Data Engineer jobs in Israel

JLL empowers you to shape a brighter way. Our people at JLL are shaping the future of real estate for a better world by combining world class services, advisory and technology for our clients. We are committed to hiring the best, most talented people and empowering them to thrive, grow meaningful careers and to find a place where they belong. Whether you’ve got deep experience in commercial real estate, skilled trades or technology, or you’re looking to apply your relevant experience to a new industry, join our team as we help shape a brighter way forward. Senior Data Engineer – Job Description Role summary: As a Senior Data Engineer, you will lead the development of scalable data pipelines and integration of diverse data sources into the JLL Asset Beacon platform. Your work will focus on consolidating financial, operational, and leasing data into a unified platform that delivers accurate insights for commercial real estate asset management. Collaborating closely with internal developers and stakeholders, you will gather requirements, solve integration challenges, and ensure seamless data flows to support informed decision-making. In addition to technical responsibilities, you will mentor junior engineers, promote best practices in data engineering and maintain high-quality standards through code reviews. Leveraging tools like Spark, Airflow, Kubernetes, and Azure, you will enhance the platform's performance, reliability, and scalability. Your expertise in data ecosystems will play a critical role in driving innovation and enabling advanced data-driven solutions for the evolving needs of the real estate industry. Company bio: JLL Asset Beacon is transforming commercial real estate asset management through data integration and innovation. Our SaaS platform consolidates and reconciles data across financial, operational, and leasing functions, creating a single source of truth. By providing real-time, end-to-end visibility into asset, fund, and portfolio performance, we empower real estate professionals to make faster, more informed decisions. With robust data visualization and reporting capabilities, our platform simplifies complex data ecosystems, enabling seamless collaboration and unlocking opportunities for value creation. Responsibilities: • Data pipeline development• Design and implement scalable, efficient, and robust data pipelines • Data platform management• Support and main the data platform to ensure reliability, security, and scalability. • Collaborate with internal developers and stakeholders• Work closely with internal developers and stakeholders to gather requirements, deliver insights, and align project goals. • Mentorship and leadership• Mentor junior engineers, fostering their growth through knowledge sharing and guidance • Conduct code reviews to maintain quality and consistency Our Technologies: • Data Processing: Spark • Workflow Orchestration: Airflow • Containerization: Kubernetes • Cloud: Azure • Data APIs and Semantic Layer: CubeJS The Candidate: • Educational Background: A STEM degree, preferably in Computer Science or Computing. • Professional Experience: At least 5 years of experience in data engineering, data warehousing, or a related field. • Technical Proficiency:• Strong Python and PySpark experience • SQL skills are essential • Experience with data orchestration platforms or tools such as Airflow, ADF, or SSIS • Hands on experience using AI powered development tools (e.g. AI coding assistants, code generation or review copilots) to build, test, and ship production code, and comfort applying AI/ML techniques within data pipelines and platform features • Data Expertise:• Solid understanding of data modeling principles and data warehousing concepts. • Domain Knowledge: Financial or real estate experience is advantageous but not required. Location: On-site –TEL AVIV, ISR If this job description resonates with you, we encourage you to apply even if you don’t meet all of the requirements. We’re interested in getting to know you and what you bring to the table! At JLL, we harness the power of artificial intelligence (AI) to efficiently accelerate meaningful connections between candidates and opportunities. Using AI capabilities, we analyze your application for relevant skills, experiences, and qualifications to generate valuable insights about how your unique profile aligns with the specific requirements of the role you're pursuing. JLL Privacy Notice Jones Lang LaSalle (JLL), together with its subsidiaries and affiliates, is a leading global provider of real estate and investment management services. We take our responsibility to protect the personal information provided to us seriously. Generally the personal information we collect from you are for the purposes of processing in connection with JLL’s recruitment process. We endeavour to keep your personal information secure with appropriate level of security and keep for as long as we need it for legitimate business or legal reasons. We will then delete it safely and securely. For more information about how JLL processes your personal data, please view our Candidate Privacy Statement. For additional details please see our career site pages for each country. Jones Lang LaSalle (“JLL”) is an Equal Opportunity Employer and is committed to working with and providing reasonable accommodations to individuals with disabilities. If you need a reasonable accommodation because of a disability for any part of the employment process – including the online application and/or overall selection process – you may email us at [email protected]. This email is only to request an accommodation. Please direct any other general recruiting inquiries to our Contact Us page > I want to work for JLL.

Location Our Data Engineer will be an integral part of our Attribute Engineering teams. This role is based fully on-site from the Attribute Tel Aviv office, located in Carlibach St 29 Tel Aviv, center. Who We Are DoiT is a global technology company that works with cloud-driven organizations to leverage the cloud to drive business growth and innovation. We combine data, technology, and human expertise to ensure our customers operate in a well-architected and scalable state - from planning to production. Delivering DoiT Cloud Intelligence, the only solution that integrates advanced technology with human intelligence, we help our customers solve complex multicloud problems and drive efficiency. With decades of multicloud experience, we have specializations in Kubernetes, GenAI, CloudOps, and more. An award-winning strategic partner of AWS, Google Cloud, and Microsoft Azure, we work alongside more than 4,000 customers worldwide. About Attribute™ Meet Attribute™: AI tokenomics without tags, SDKs, or code changes. A lightweight eBPF sensor installs in 15 minutes and starts producing per-customer, per-feature, and per-agent cost the same day. No instrumentation. No tagging policy. No engineering lift. The problem it solves is real and measurable. In DoiT's survey of 500 finance and technology leaders, only 15% said they could calculate AI ROI without significant bottlenecks — and 79% experienced AI-related cost overruns in the past 12 months. AI spend is tripling. Visibility isn't keeping up. Attribute™ fixes that, at the kernel level, with nothing to instrument. The Opportunity Attribute technology and services are heavily based on eBPF technology on the Attribute sensor side and extensive ETL and data processing on the Backend (based on GCP). In order to meet the increasing challenges of the growing business, we are seeking an experienced engineer who will be working closely with our product on one hand and with the Frontend team on the other, and will be responsible for development of new capabilities as well as operational aspects of services you develop. Responsibilities • Implementing features. From proposal through spec and implementation to maintenance. You're expected to propose things you think can be an excellent addition to the products. • Reviewing code. We believe in code reviews, and you'll soon start reviewing pull requests as well. • Providing feedback. The team plans and discusses upcoming work. We provide feedback to each other, trying to find challenges and unknowns as early as possible. • Working AI-augmented. Use AI daily across your workflow, exploring unfamiliar codebases, prototyping, debugging, writing tests, and documentation. • Collaborating cross-functionally. Work with product, support, and other engineers to understand where the gaps hurt, and bring your own ideas to the table rather than waiting for a spec. Qualifications • 3+ years of hands-on experience in data engineering, backend engineering, or a similar field • 2+ years of practical experience with Python, Spark, and PySpark • Experience building ETL processes and working with big data technologies such as Pub/Sub • Familiarity with Terraform and CI/CD methodologies • Experience building or operating data pipelines in a SaaS production cloud environment • Versatile developer who learns new tools and technologies quickly, uses AI effectively, and applies sound engineering judgment • Strong collaborator and independent contributor with excellent communication skills • Growth minded, pragmatic problem solver who simplifies complexity and iterates quickly from MVPs using data and feedback • Excellent communication skills in English, both written and verbal • Self-organized, goal-oriented and self-motivated; confident, thorough and tenacious Bonus Points • BA/BS degree or equivalent practical experience • Experience with C++ or C# • Familiarity with Google Cloud Platform Are you a Do’er? Be your truest self. Work on your terms. Make a difference. We are home to a global team of incredible talent who work remotely and have the flexibility to have a schedule that balances your work and home life. We embrace and support leveling up your skills professionally and personally. What does being a Do’er mean? We’re all about being entrepreneurial, pursuing knowledge and having fun! Click here to learn more about our core values. Sounds too good to be true? Check out our Glassdoor Page. We thought so too, but we’re here and happy we hit that ‘apply’ button. • Unlimited Vacation • Flexible Working Options • Health Insurance • Parental Leave • Employee Stock Option Plan • Home Office Allowance • Professional Development Stipend • Peer Recognition Program Many Do’ers, One Team DoiT unites as Many Do’ers, One Team, where diversity is more than a goal—it's our strength. We actively cultivate an inclusive, equitable workplace, recognizing that each unique perspective enhances our innovation. By celebrating differences, we create an environment where every individual feels valued, contributing to our collective success. #LI-Remote

Description About Immunai: Immunai is an AI-driven platform company focused on improving drug discovery and development by decoding the human immune system. We combine large-scale single cell immune data, advanced machine learning, and strong engineering to help pharmaceutical and research partners make better, more informed decisions throughout the drug development process. Our long-term goal is to reduce drug development failure rates and help more effective medicines reach patients. We’re building this platform thoughtfully and collaboratively, bringing together expertise across biology, AI, engineering, and business. Immunai is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. About the role: We are looking for an experienced Data Infrastructure Team Lead to lead our Data Infrastructure team. In this role, you will have formal people-management responsibility for a multidisciplinary team that builds, productionizes, and improves big data and analytics infrastructure. You will be responsible for team delivery, combining technical depth, agile leadership, and an AI-first mindset to help the team build reliable systems, improve how it works, and continuously raise its engineering standards. Location: Ramat Gan (Bursa area), Israel - Hybrid model What will you do? • Lead, manage, and develop a data infrastructure team of approximately 5-7 people. • Take responsibility for team delivery, including planning, prioritization, execution, and continuous improvement. • Lead agile ways of working, including scrum-based delivery practices. • Guide the design, productionization, and ongoing improvement of big data and analytics infrastructure. • Partner closely with cross-functional stakeholders across technical, scientific, and business interfaces. • Help the team adopt AI-first engineering practices, including automation and AI-assisted development workflows. • Drive improvements in team processes, technical quality, delivery predictability, and collaboration. • Support architectural and technical decisions across cloud infrastructure, data pipelines, orchestration, and production systems. • Create an environment where team members can grow, contribute, and improve together. Requirements Required qualifications: • 5+ years of experience leading data engineering, data infrastructure, or related engineering teams, of 5+ people - a must • Strong technical background in data infrastructure, cloud computing, and production systems - a must • Hands-on experience with data warehousing tools such as Snowflake or BigQuery, and data pipeline orchestration tools such as Dagster or Apache Airflow - a must • Experience developing in Python • Experience productionizing big data, analytics, or data platform infrastructure • Experience leading agile teams and working with scrum methodologies • Demonstrated ability to lead multidisciplinary teams and collaborate effectively across interfaces. • Track record of helping teams improve how they work, including process improvement, automation, technical quality, or delivery practices. • Strategic mindset with the ability to connect technical decisions to team and business goals. • Strong English communication skills, written and spoken, for working with an international and multilingual team. Preferred qualifications: • Experience working in a scientific domain. • Experience in biotech, immunology, life sciences, or another biology-adjacent domain. • Experience with agentic AI concepts, tools, or development patterns. • Experience helping software or data engineering teams transition toward AI-first development processes. • Familiarity with modern automation practices across engineering workflows, infrastructure, and delivery pipelines. Desired personal traits: • AI-first and automation-oriented mindset. • Strong people's leadership instincts and a genuine drive to help others improve. • Collaborative, clear, and thoughtful communication style. • High ownership, good energy, and comfort operating across disciplines. • Curious, pragmatic, and able to balance strategy with hands-on technical judgment. When you apply for a role at Immunai, we process your personal data (such as CV, contact details, and professional background) to assess your suitability for current and future roles. Your information may be shared internally with relevant employees and stored or processed by trusted service providers, some of whom may be located outside your country of residence. You can read more about how we process data here: https://www.immunai.com/privacy-policy/.

Speedata is modernizing analytics infrastructure with the first purpose-built ASIC processor, the Analytics Processing Unit (APU), for analytics and AI data workloads. Delivering up to 100x faster Apache Spark performance while cutting infrastructure TCO by 90%, the APU executes analytics operations directly in silicon with seamless integration and no code changes. In this role, you will be responsible for building data infrastructure for performance tuning, and analysis of a new analytics product. As a member of our Data Performance team, you will collaborate closely with other SW & HW Engineers to improve the performance of our new cutting-edge APUs. You will collaborate with our business leaders and participate in the product design and implementation. You will evaluate, implement, and integrate a diverse set of tools and technologies such as Spark, Comet, Velox, Dagster, Hardware emulators and software simulators. Join a multi-disciplinary team of experts operating at the foundation of Speedata's data infrastructure stack Build a robust data benchmarking infrastructure Develop in-house measurements and ETL tools Conduct detailed performance analysis and characterization Research state-of-the-art benchmarks and techniques for SQL and data optimization BS degree in Computer Science +5 years of experience in a Data Engineering role +5 years of experience of programming +2 years of experience of SQL Tuning and Data Pipeline In depth knowledge of SQL Experience with SQL benchmarks, specifically TPC-H and TPC-DS Experience with GPUs or other hardware accelerators

Description About DoorLoop DoorLoop is property management software built for speed and the smart choice for people who take growth seriously. With offices in Miami, New York City, and Tel Aviv, we’re a global company helping property owners and managers move faster, scale smarter, and get real support, real fast. We’re proudly People First. That’s why we’re a Certified Great Place to Work, recognized by Forbes as one of America’s Best Startup Employers in both 2024 and 2025, and earn top ratings on Glassdoor. We’re growing quickly and looking for a Motion Designer to help elevate our brand in the market. Mission DoorLoop is looking for a Senior Data Engineer to co-own our data platform as its second engineer. Part of the foundation is in place: a layered dbt project on Snowflake, a semantic layer that defines our core business metrics once, and an AI data assistant that answers business questions from it. Much of it is still being designed, and you will help build it. You will take design decisions with our founding data engineer, own whole business domains end to end, and raise the bar on modeling, reliability, and review as more of the company depends on the platform. You will also build data products with AI: our AI data assistant, internal dashboards, and the data apps that come next, built AI-first and tested so their answers can be trusted. You will work directly with Finance, GTM, and CX leaders on the metrics that run the business, and with analysts who ship their own dbt changes, helping them do it well. This role is for an experienced engineer who wants to shape the foundation while it is still being built: open-minded, willing to push back on the right questions, and ready to make design decisions and own them. Responsibilities • Own core business domains end to end (GTM, CX, and Finance), from the stakeholder conversation to the model, the metric, and the dashboard or AI answer built on it • Help build the foundation: take design decisions with the founding engineer on modeling patterns, incremental strategy, ingestion design, semantic-layer structure, and warehouse cost • Lead metric-definition work with business leaders: settle contested definitions, document them, and get sign-off • Own platform reliability: testing strategy, monitoring and alerting, the incident process, and root-cause fixes • Design and build ingestion for new sources, choosing the right pattern (Fivetran, Airbyte, or custom n8n → S3 → Snowpipe pipelines) • Reconcile financial data (Stripe payments and payouts) to its source of truth, and own the checks that keep revenue numbers right • Extend the semantic layer: definitions, descriptions, and verified queries, so every tool gives the same answer • Build data products with AI: the AI data assistant that answers business questions, internal dashboards, and new data apps. Design them AI-first, and build the evaluation sets that prove their answers are correct • Set the standard for code review, and mentor the analysts who ship their own dbt changes • Use AI tools every day, and build the shared skills and workflows the data team relies on Requirements • 5+ years in data engineering or analytics engineering, including at least 2 years owning a production data warehouse or dbt project • Expert SQL and deep experience with a cloud data warehouse (Snowflake preferred), including performance and cost • You have designed and led a production dbt project: structure, conventions, testing, and CI • You have built and run ingestion pipelines, with managed tools and with your own code • You have owned data reliability: monitoring, alerting, incident response, and the fixes that follow • You have led metric-definition work with senior non-technical stakeholders, such as Finance • Strong Python for pipelines, automation, and tooling • You review other people’s code and mentor less experienced colleagues • You use AI tools (Claude, Cursor, or similar) every day, with specific workflows you can describe and defend • You want to build data products with AI, not only use AI to write code • Open-minded: you ask before you assume, and you change your mind when the evidence says so • You push back on the right questions, and you make design decisions and own them • Clear, direct communicator, in writing and in conversation Bonus Points • Built or owned a semantic layer (Snowflake Semantic Views, dbt Semantic Layer, Cube, LookML, or similar) • Payments or financial data: Stripe, revenue recognition, reconciliation, month-end close • Shipped a data product with AI: an AI assistant, text-to-SQL, an LLM feature on data, or evaluation sets for AI answers • Orchestration and automation tools (n8n, Airflow, Dagster, or similar) and AWS Benefits What We Offer • Hybrid work model (4 days in office, 1 WFH day) • Unlimited paid time off • Cibus meal card • Private health insurance subsidy • Pension, Keren Hishtalmut & Dmei Havraa • Real impact at scale — product used daily by thousands of paying customers • Certified Great Place to Work · Forbes America's Best Startup Employers 2024 & 2025 Equal Opportunity Employer & AI DoorLoop is an equal opportunity employer and does not discriminate on the basis of race, color, religion, sex, sexual orientation, gender identity or expression, national origin, age, disability, veteran status, marital status, pregnancy, genetic information, citizenship status, or any other characteristic protected by applicable law. We use AI-assisted tools, including assessment tools that evaluate cognitive ability and personality fit, to help evaluate applications. Human oversight is maintained and no hiring decision is made solely by an automated system. For positions that can be performed in New York City, candidates may request an alternative selection process. Applicants with disabilities may also request reasonable accommodation at any stage of the hiring process. For any of these requests please contact [email protected]. For more information about the tools we use, bias audit results, and how we collect and protect applicant personal data, please review our Applicant Privacy Notice.

Description Trigo is Crafting Tomorrow's Retail Experience We started with a simple question: How can vision AI make shopping better for everyone? Today, our team of passionate experts is transforming how people shop and how retailers operate, one store at a time. Our goal is to solve real retail challenges by developing advanced computer vision AI that prevents loss, enables grab-and-go shopping, and turns store data into valuable insights, all while delivering clear value from day one. With multiple global deployments, deep partnerships with leading retailers, and a product suite that’s proving its impact every day, Trigo isn’t just imagining the future of retail, we’re building it. We are looking for an experienced Data Engineer to own and evolve Trigo’s data infrastructure and analytics platform. You will design and build scalable data pipelines and data models, working with large and diverse datasets generated across Trigo’s global retail deployments. You will own the data lifecycle from ingestion and transformation through orchestration, reliability, and analytics-ready datasets. As a key technical owner of Trigo’s data platform, you will also work closely with analysts, Product, R&D, Operations, and Customer Success to build trusted data products, evolve our BI semantic layer, and turn complex data into scalable solutions A day in the life • Design, build, and maintain scalable ETL/ELT pipelines processing large and diverse datasets. • Own and evolve Trigo’s data architecture, from ingestion and transformation through analytics-ready data models and consumption. • Build reliable data workflows and orchestration processes, with a focus on scalability, performance, and maintainability. • Design and maintain curated data models that power analytics, operational workflows, and data-driven products. • Ensure data quality, observability, monitoring, and reliability across datasets and pipelines. • Develop and evolve the BI semantic layer, enabling trusted metrics and self-service analytics across the company. • Work closely with R&D and Product on data integrations and new data-driven capabilities, including use cases that bridge offline analytics and production systems. • Partner with analysts and business stakeholders to translate complex requirements into scalable data solutions. You bring to the table • 4+ years of experience as a Data Engineer, Analytics Engineer, or similar hands-on data role • Strong command of SQL and proficiency in Python for data modeling and transformation • Experience with modern data tools such as dbt, BigQuery, and Airflow (or similar) • Proven ability to design clean, scalable, and analytics-ready data models • Familiarity with BI modeling and metric standardization concepts • Experience partnering with analysts and stakeholders to deliver practical data solutions • A pragmatic, problem-solving mindset and ownership of data quality and reliability • Excellent communication skills and ability to connect technical work with business impact Nice to have • Experience implementing or managing BI tools such as Tableau, Looker, or Omni. • Understanding of retail, computer vision, or hardware data environments. • Exposure to time-series data, anomaly detection, or performance monitoring. • Interest in shaping a growing data organization and influencing its direction.

ABOUT PLACER.AI: Placer.ai is transforming how organizations understand the physical world. Our location analytics platform provides unprecedented visibility into locations, markets, and consumer behavior. Placer empowers thousands of customers—from Fortune 500 companies, to local governments and nonprofits— to make smarter, data-driven decisions. What sets us apart? We've built the most advanced location intelligence platform in the market while maintaining an uncompromising commitment to privacy, proving that powerful analytics and responsible data practices can coexist. Our growth reflects the market's demand: we reached $100M in annual recurring revenue within just 6 years of launching, achieved unicorn status with a $1B+ valuation in 2022, and continue to expand rapidly as one of North America's fastest-growing tech companies. We're creating a $100B+ market opportunity, and we're just getting started. Named one of Forbes America's Best Startup Employers and a Deloitte Technology Fast 500 company, we're building a culture where innovation thrives, collaboration is the norm, and every team member contributes to reshaping how the world understands location. SUMMARY: As a Senior Big Data Engineer, working within Placer.ai's Mobility Group, you will play a pivotal role in designing, developing, and maintaining the data infrastructure that powers our location analytics platform. RESPONSIBILITIES: • Data Pipeline Architecture and Development: Design, build, and optimize robust and scalable data pipelines to process, transform, and integrate large volumes of data from various sources into our analytics platform. • Data Quality Assurance: Implement data validation, cleansing, and enrichment techniques to ensure high-quality and consistent data across the platform. • Performance Optimization: Identify performance bottlenecks and optimize data processing and storage mechanisms to enhance overall system performance and reduce latency. • Cloud Infrastructure: Work extensively with cloud-based technologies (GCP and AWS), to design and manage scalable data infrastructure. • Collaboration: Collaborate with cross-functional teams including Data Analysts, Data Scientists, Product Managers, and Software Engineers to understand requirements and deliver solutions that meet business needs. • Data Governance: Implement and enforce data governance practices, ensuring compliance with relevant regulations and best practices related to data privacy and security. • Monitoring and Maintenance: Monitor the health and performance of data pipelines, troubleshoot issues, and ensure high availability of data infrastructure. • Mentorship: Provide technical guidance and mentorship to junior data engineers, fostering a culture of learning and growth within the team. REQUIREMENTS: • Strong hands-on Apache Spark experience — building and operating pipelines in production, not just familiarity • Proficiency in PySpark or Scala for Spark development • Proven track record delivering ETL pipelines and data integration at scale • Solid SQL skills and command of data modeling concepts • Cloud platform experience (AWS, GCP, or Azure) in a production data context • Comfortable working with distributed systems and big data formats (Parquet, Delta Lake) Nice to have: • Experience with pipeline orchestration tools, particularly Apache Airflow • Exposure to the geospatial or location analytics domain • Familiarity with Hadoop ecosystem components • Background in both Python and Scala (beyond Spark context) WHY JOIN PLACER.AI? • Join a rocketship! We are pioneers of a new market that we are creating • Take a central and critical role at Placer.ai • Work with, and learn from, top-notch talent • Competitive salary • Excellent benefits NOTEWORTHY LINKS TO LEARN MORE ABOUT PLACER • Placer.ai's $100M round C funding (unicorn valuation!) • See our data in action at The Anchor • Placer.ai in the news • Video: About Placer for Commercial Real Estate • Video Playlist: Placer Brand & Explainer Videos Placer.ai is committed to maintaining a drug-free workplace and promoting a safe, healthy working environment for all employees. Placer.ai is an equal opportunity employer and has a global remote workforce. Placer.ai’s applicants are considered solely based on their qualifications, without regard to an applicant’s disability or need for accommodation. Any Placer.ai applicant who requires reasonable accommodations during the application process should contact Placer.ai’s Human Resources Department to make the need for an accommodation known. May 2026

Simply's mission is to make the pursuit of creative hobbies simple and fun for all. Our top-grossing apps Simply Piano, Simply Guitar, Simply Sing, and Simply Draw put us on the fast track to building the world's largest consumer subscription service for creative learning. With over a million monthly downloads and hundreds of thousands of daily learners, we're building the AI creative companion for every home. As a Data Engineer You Will: • Design, develop, scale, and optimize the data pipelines, ETLs and platform components (inc infra for analytics AI) • Implement and support robust, scalable data solutions from different sources to enhance business analysis capabilities. This includes implementing technologies from scratch and continuously exploring best practices and tools. • Help to improve our analytics work. By getting better data, making it more trustworthy and accessible and help nurturing top-grade data culture in the company. • Collaborate with various stakeholders across the company to translate requirements into high-quality data pipelines and models Who are you? • Have 5+ years of experience as a BI Developer or Data Engineer including ETL design, implementation, optimization and maintenance. • Experienced in writing complex SQL queries, Data Modeling, and Python. • Proven record of merging multiple data sources to develop a single source of truth for reporting needs • Experience working with CI/CD systems • Excellent communication skills and comfortable working in a multi-disciplinary team • Experience preparing data for business intelligence tools such as Tableau • Bachelor’s or Master’s Degree in Computer Science, Information Systems or a related field • An independent, self-learner who is passionate about data • Understands business processes and can translate business needs into software solutions • Knowledge of metadata management, data lineage, and principles of data governance • A team player with amazing verbal and written communication skills Bonus Points if you have: • Understanding of current marketing analytics topics including attribution and experience with advertising campaign management/buying platforms. • DBT experience. • Advanced Snowflake skills.

Description About Quicklizard Quicklizard is a dynamic pricing platform used by leading retailers, marketplaces, and e-commerce brands worldwide. Our engine ingests sales, competitor, inventory, and cost data and turns it into real-time pricing recommendations - processing billions of records a day across multi-region pipelines that never stop running. The Role We're looking for a Data Engineer to own our data architecture end-to-end. You'll design, build, and scale the pipelines that power every pricing decision we make - from raw ingestion through our data lake to the analytics and BI layers our customers rely on. This is a hands-on leadership role: you'll set technical direction, drive architectural decisions, and mentor a team of data engineers, while still writing code and owning delivery. What You'll Do • Architect and build large-scale batch and streaming ETL/ELT pipelines • Own data lake design, table modeling, and partitioning strategy across billion-row datasets • Drive query performance and cloud cost optimization across AWS and GCP • Establish data quality, observability, and reliability standards - freshness, correctness, and SLAs • Partner with backend, product, and data science teams to expose data through internal and customer-facing APIs Our Stack Spark / EMR · Airflow · BigQuery · PostgreSQL & Aurora · Kafka · RabbitMQ · Elasticsearch · Go · Python · AWS · GCP · Kubernetes · Terraform What We're Looking For • 5+ years in data engineering, with real production experience at scale (terabytes+, billions of rows) • Deep SQL and strong distributed-processing experience (Spark or equivalent) • Strong Python and/or Go • Hands-on experience with cloud data warehouses (BigQuery, Snowflake, Redshift) and orchestration tooling • AI-first mindset - you actively work with AI coding tools (Claude Code, Cursor, Copilot) and LLM-based agents as part of your day-to-day, and look for opportunities to automate and accelerate engineering work with them • Experience building or supporting AI/LLM-driven data products - pipelines that feed models, agents, or ML systems • Product mindset: you care why the data is being used, not just that the job finished green Nice to have: streaming architectures, cost/FinOps ownership, multi-region or multi-cloud systems, e-commerce or pricing domain experience, MCP servers or agentic tooling.

Description Appdome's mission is to protect every mobile app in the world and the people who use them. We are the leader in AI-native mobile business protection, providing cyber and fraud teams with an agentic platform that builds, monitors, and maintains security defenses in Android and iOS apps — with no SDKs, no coding, and no disruption to engineering cycles. Our platform delivers over 400 security, anti-fraud, anti-bot, and API protection capabilities, powered by deep learning models trained on a decade of mobile defense data and trillions of live threat events. From build time to runtime, Appdome's AI Agents help mobile brands detect, investigate, and respond to threats faster than ever — recognized as the best AI Platform for Cyber Resilience at RSA Conference 2026 for the second consecutive year. Leading financial, healthcare, m-commerce, and B2B brands rely on Appdome to secure over 50,000 mobile apps and protect more than 1 billion end users globally. Appdome is an Equal Opportunity Employer. We are committed to diversity, equity, and inclusion in our workplace. We do not discriminate based on race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, veteran status, or any other characteristic protected by law. All qualified applicants will receive consideration for employment without regard to any of these characteristics. About the Role  We're growing our Data team and looking for a Data Engineer who lives and breathes data. At Appdome, data moves fast and at scale: trillions of live threat events feeding real-time detection, risk scoring, and response. This role is about designing data so it stays fast under heavy volume: the right architecture, models, and storage choices to keep latency low and throughput high. You'll own data systems end to end, from ingest to serving, and have real influence over how we build. What You’ll Do  • Design, build, and maintain scalable, low-latency data pipelines, ETL/ELT, and infrastructure. • Architect data models, schemas, and storage layouts optimized for fast retrieval at large volume. • Build real-time / event-driven ingestion and processing for high-throughput threat and risk data. • Optimize SQL and NoSQL databases - query tuning, indexing, partitioning, cost/performance tradeoffs. • Work with big-data volumes across pipelines, data lakes, and warehouse / lakehouse layers, using Spark for large-scale processing and enrichment. • Own data observability - pipeline health, freshness, and quality. • Collaborate with software engineers, security experts, and data scientists to integrate data into Appdome's products. Requirements • B.Sc. in Computer Science, Data Engineering, or a related field. • 3+ years hands-on with large-scale data infrastructure. • Strong Python (including Pandas). • Deep SQL and NoSQL knowledge, with real performance-optimization experience. • Proven experience with real-time/low-latency systems, and the data architecture and modeling instincts that make them fast. • Comfort with big-data volumes, pipelines, and data lakes. • Experience with streaming / event-driven design (e.g., Kafka). • Spark / PySpark for large-scale processing, or a strong adjacent big-data background. • Strong problem-solving skills and a proactive, independent mindset. Advantages  • Experience with ClickHouse. • Data warehousing and lakehouse / open table formats (e.g., Apache Iceberg). • Vector databases and embeddings - storing and serving them to support AI and data-science features (e.g., pgvector). • Strong system design and data architecture sense - knows how to build the data model the right way. • Experience using AI-assisted development tools (e.g., Cursor, Claude Code) in day-to-day work. • Experience with security, fraud, or other high-volume telemetry data. • Comfort with containerized infrastructure (Docker, basic Kubernetes) and light DevOps (CI/CD, Git). • ElasticSearch, Redis, DynamoDB, or Metabase. Who you are  • Independent and self-driven - comfortable owning systems end to end. • Growth-oriented - eager to develop and take on more over time. • Collaborative - communicates well across engineering, security, and data science. • Adaptable - thrives in a fast-paced environment with a can-do attitude.

Description About the role & team Our DevOps team builds and operates the production streaming infrastructure that powers the company’s real-time data ecosystem. The team owns Apache Kafka, Kafka Connect, Schema Registry, Elasticsearch, Kibana, and the supporting Linux, Windows, Kubernetes, observability, and automation layers across hybrid cloud and on-premises environments. As a DevOps & Data Engineer, you will own platform availability, performance, upgrades, capacity, incident response, and infrastructure automation. You will operate the underlying platforms, not only develop applications or pipelines that consume them. We're a collaborative, high-impact team that values ownership, technical excellence, and continuous learning. Every engineer plays a meaningful role in designing reliable, scalable systems while contributing to a culture of knowledge sharing and teamwork. If you're passionate about distributed systems, infrastructure engineering, automation, and solving complex technical challenges—we'd love to meet you. What you'll be doing • Build, operate, and maintain our core data infrastructure platforms, including Apache Kafka, Kafka Connect, Elasticsearch, SchemaRegistry and Kibana. • Design, deploy, and monitor scalable real-time data pipelines across on-premises and cloud environments. • Troubleshoot production issues, participate in incident response, perform root cause analysis, and drive long-term reliability improvements. • Develop automation, Infrastructure-as-Code solutions, and operational tooling to improve platform efficiency and reduce manual effort. • Build and maintain internal tools, APIs, and self-service capabilities for engineering and data teams. • Collaborate closely with Software Engineers, Data Engineers, Analysts, and Platform teams to ensure reliable data delivery. • Implement and maintain monitoring, alerting, and observability solutions using Prometheus and Grafana. • Support platform upgrades, infrastructure improvements, and capacity planning initiatives. • Contribute to documentation, knowledge sharing, and engineering best practices to continuously improve operational excellence. Requirements What we're looking for Technical expertise • Hands-on experience with Apache Kafka clusters, Kafka Connect, and Schema Registry (Apache or Confluent). • Strong Linux & Windows administration, troubleshooting, shell scripting, and performance tuning skills. • Strong experience with Elasticsearch and Kibana. • Experience working with CI/CD pipelines, Git, and Infrastructure-as-Code tools such as Terraform or Ansible. • Production Kubernetes and Docker experience, including troubleshooting, storage, networking, RBAC, and resource management. • Proficiency in Python (or a similar language) for automation, infrastructure tooling, and operational services. • Experience implementing monitoring and observability solutions using Prometheus and Grafana. Knowledge • Strong understanding of distributed systems and event streaming architectures. • Solid understanding of DevOps principles, Infrastructure-as-Code, and automation practices. • Familiarity with cloud infrastructure (AWS, GCP, or Azure) and hybrid cloud/on-premise architectures. • Understanding of production operations, monitoring, incident management, and operational best practices. • Familiarity with infrastructure security, access control, and secrets management. Experience • 3+ years of experience working as Platform Engineering, SRE, DevOps, or production streaming infrastructure. • Proven experience operating and supporting production systems with a strong focus on reliability and scalability. • Experience troubleshooting distributed systems and production incidents. • Experience working in cross-functional environments alongside Software Engineers, Data Engineers, and Platform teams. • Experience building, operating, and improving data platforms and streaming pipelines in production. Nice to have • Experience with Apache Flink or other stream processing technologies. • Experience with Microsoft SQL Server (MSSQL). • Experience building self-service platforms or developer enablement solutions for engineering or data teams. What we offer: Our roles offer more than just a job; you’ll become part of the evoke family! We have created an environment where our people can thrive. Check out some of the fantastic benefits on offer: • Hybrid work model • Free parking in the building + free electric car charging • Broad collective health insurance (with options for family members and extensions) • Birthday gift + day off during your birthday month • Refer a friend - bonus or gift card • HitechZone membership • Gifts on holidays and life events • Ten Bis More about evoke We’re a business that embraces change and progress. The power behind big-name brands William Hill, 888 and Mr Green, evoke is the new name for 888 Holdings. Marking a new sense of purpose, direction and ambition for the business, there couldn’t be a more exciting time to join us as we accelerate our journey to bring even greater delight to our customers with world-class experiences. That’s the future. That’s evoke. At evoke, you’ll benefit from flexibility and a culture built on trust. We’ll give you the space to be yourself and the tools you need to protect our customers while they play. We’ll invest in your future to help you develop your unique strengths and build a career that’s right for you. Apply At evoke, we prioritize diversity, equity, and inclusion for the benefit of our company, employees, and communities. We foster a welcoming and safe workplace that values all forms of diversity and provides opportunities for growth. Sounds good? Then you belong at our place! The first step in the recruitment process is kickstarting your application, followed by an initial screening call and an interview stage. Apply today to kickstart your application with evoke!

Description Join Noma Security and help shape the future of AI security in a fast-paced, high-impact environment. Noma is building the first comprehensive AI Security and Governance Platform, helping organizations adopt AI and LLMs with confidence and control. As AI becomes core to modern enterprises, we provide seamless visibility and protection across the entire AI lifecycle. Our team works at the intersection of AI, security, and cloud, shaping a new category in a rapidly evolving market. At Noma, you’ll have the opportunity to make a meaningful impact while working with exceptional people on technology that truly matters. As Noma's Founding Data Engineer, you will be the first dedicated Data Engineer at the company, with the opportunity to build our data engineering function from the ground up. You'll own the architecture and foundations of Noma's internal data platform - the central warehouse, pipelines, and models every team relies on to understand how our product is performing, and provide tools for day to day operations. You'll define how data from across the company is collected, modeled, transformed, and governed, and establish the standards and best practices that will scale with Noma as we grow. Working closely with Engineering, Data Science, Delivery, Product, and Analytics teams, you'll turn data into reliable, structured assets that power product and business decisions. 🛠️ What You’ll Do • Build Noma’s Data Engineering Function: Be the first dedicated Data Engineer at Noma and will be required to be opinionated about the warehouse architecture, tooling, standards, and best practices for how we work with data across the company. • Develop Data Pipelines: Design, build, and maintain data pipelines that transform company data into structured, queryable assets • Enable Data-Driven Decisions: Partner with Engineering, Data Science, Product and Analytics teams to deliver trusted data foundations and actionable insights. • Create BI Dashboards: Build and maintain dashboards and reporting layers that support product, and operational decision-making • Ensure Data Quality and Accessibility: Implement best practices for data modeling, governance, monitoring, and reliability ✅ What You Bring • 5+ years of experience in Data Engineering roles • Proven experience designing and building data infrastructure from the ground up, with the ability to independently drive architecture and technology decisions. • 3+ years of experience working with modern data warehouse technologies such as Snowflake or Databricks • Strong SQL skills and experience working with large-scale datasets • Experience creating data models and BI dashboards serving business, product, or analytics teams • Strong understanding of data architecture, performance, and scalability considerations • Ability to work cross-functionally with technical and non-technical stakeholders • Strong ownership mindset and a pragmatic approach to problem solving 🎯 Nice to Haves • Experience working closely with Data Science teams • Background in cybersecurity, infrastructure, deep tech, or AdTech environments • Experience as an early or first Data Engineer at a startup, or building a data platform from an early stage. • Familiarity with modern data orchestration and transformation tools 💙 Perks & Benefits • Located in a prime area with easy access to public transportation, near the Hashalom train station and the Light Rail. • A bright, spacious, dog-friendly office that makes you smile the moment you walk in 🐶 • Team bonding activities, company retreats, happy hours, and holiday gifts • Pilates classes at the office 💪🧘‍♀️ • Never hungry: Monthly lunch budget, dinners provided, and a fully stocked kitchen 🍽️ • A warm, supportive, and people-first company culture • Pension & Keren Hishtalmut (advanced training fund) • A global work environment with teams across Tel Aviv, the US, the Netherlands, and London • Options that let you share in Noma’s growth and success

Transmit Security gives businesses the modern tools they need to build secure, trusted and end-to-end digital identity journeys to innovate and grow. CX-focused, cybersecurity conscious leaders rely on Transmit Security’s xCIAM platform to provide their customers with smooth experiences protected from fraud across all channels and devices. Transmit Security serves many of the world’s largest banks, insurers, retailers, and other leading brands, collectively responsible for more than $1.3 trillion in annual commerce. About the Role: Transmit Security is a top player in its game and is heading for an exciting year. In this role, you will take an integral part in the creation of a new and innovative SaaS product. If you are a talented software engineer that likes to solve complex problems and looking for your next challenge we want you to join our team! What you’ll do: As the Team Leader at Transmit Security, you will lead a talented team to design, implement, and deploy scalable data solutions for an innovative SaaS product. You’ll be responsible for shaping the direction of a system that impacts millions of users worldwide. If you're an experienced manager with a strong technical background, ready to lead in a dynamic, fast-paced production environment, we want you on our team! Responsibilities: • Collaborate effectively with cross-functional teams (Data Science, Security, etc.) to ensure alignment on business needs and security standards. • Manage the technical backlog, make critical decisions on product milestones, and ensure timely, secure, high-quality delivery and deployment. • Foster the growth of team members through mentorship, personal development opportunities, and the promotion of continuous improvement. • Identify, manage, and mitigate security risks across the data platform, maintaining high standards in all initiatives. • Define and implement methodologies to guarantee the performance, scalability, and quality of our data infrastructure. What We're Looking For: • 5+ years of software engineering experience, with at least 2 years in a leadership capacity. • Extensive knowledge of distributed computing platforms (Flink, Spark, Beam) and cloud platforms (AWS, GCP, Azure). • Proficiency in programming languages such as Python, Java, Scala, or Go. • Demonstrated strong leadership abilities, including guiding teams, managing backlogs, and fostering effective cross-functional collaboration. • Proven experience in managing security risks and ensuring high-quality, scalable, and compliant systems. • Ability to maintain focus on key priorities and excel in a fast-paced, dynamic production environment. Advantages: • Bachelor’s degree in Computer Science or a related field. • Experience with microservice architecture, data management tools (Kafka, Airflow, MLOps), and CI/CD processes. • Familiarity with databases (Postgres SQL, Redis) and Kubernetes. • Background in identity management, risk assessment, or fraud detection. #LI-AM1 #LI-Hybrid

Description At UVeye, we're on a mission to redefine vehicle safety and reliability on a global scale. Founded in 2016, we have pioneered the world's first fully automated suite of vehicle inspection systems. At the heart of this innovation lies our advanced AI-driven technology, representing the pinnacle of machine learning, GenAI, and computer vision within the automotive sector. With over $380M in funding and strategic partnerships with Toyota, Amazon, General Motors, JLR, Volvo, and Hertz, our technology is deployed across manufacturing plants, dealerships, wholesale auctions, fleets, and seaports worldwide. Named one of Fast Company's Most Innovative Companies of 2026, our 300+ global employees are solutions-oriented, accountable, and driven by one shared goal: making roads safer for everyone. We are looking for an experienced Senior Data Engineer to join our Data team. In this role, you will lead and strengthen our Data Team, drive innovation, and ensure the robustness of our data/analytics platforms. A day in the life and how you’ll make an impact: • Design and develop high-performance Data Pipelines and ETL processes to support diverse business needs. • Work closely with Product, Business Intelligence, Sales and other teams to integrate data solutions, ensuring seamless alignment and collaboration across functions. • Continuously improve our data analytics platforms, optimizing system performance and ensuring robust, reliable data infrastructure. • Oversee the entire data lifecycle, from infrastructure setup and data acquisition to detailed analysis and automated reporting, driving business growth through data-driven insights. • Implement robust data quality checks, monitoring mechanisms, and data governance policies to maintain data integrity and security, troubleshooting and resolving any data-related issues efficiently. Requirements • 5+ years of hands-on experience in Data Engineering, preferably in a fast-paced startup or technology environment. • Strong experience designing, building, and maintaining scalable data pipelines and ETL/ELT workflows. • Experience with modern data engineering technologies such as Airflow, Spark, Flink, Kafka, Pub/Sub, and dbt – an advantage. • Experience with cloud data warehouses such as BigQuery or Snowflake, and strong hands-on experience with public cloud environments, preferably GCP or AWS. • Hands-on experience with GenAI technologies and AI-assisted engineering tools, applying them to development, data workflows, automation, debugging, and engineering productivity. • Strong SQL expertise and hands-on experience with relational and NoSQL databases such as MySQL, Firestore, Redis, and Elasticsearch. • Strong Python development skills. • Experience with BI and visualization platforms such as Looker or Tableau. • Strong analytical and problem-solving skills, with the ability to communicate technical ideas and insights clearly to both technical and business stakeholders. • B.Sc. in Computer Science, Information Systems Engineering, Software Engineering, or a related technical field – an advantage. • Ability to work from our Tel Aviv office 4 days a week. Why UVeye: • Pioneer Advanced Solutions: Harness cutting-edge technologies in AI, machine learning, and computer vision to revolutionize vehicle inspections. • Drive Global Impact: Your innovations will play a crucial role in enhancing automotive safety and reliability, impacting lives and businesses on an international scale. • Career Growth Opportunities: Participate in a journey of rapid development, surrounded by groundbreaking advancements and strategic industry partnerships.

About Tavily - Search API Tavily is a cutting-edge company focused on providing a powerful and efficient Search API. We empower developers and businesses by delivering high-quality, relevant search results quickly and reliably. Join our team to help build the data infrastructure that supports and scales our core product. The Role We are seeking a highly motivated and experienced Data Engineer to join our growing team. You will be responsible for designing, constructing, installing, testing, and maintaining highly scalable data management systems. You will work closely with our engineering and devops teams to build and optimize the data pipelines that are crucial to the performance and accuracy of our Search API. Responsibilities • Design, build, and maintain efficient and reliable ETL/ELT pipelines for data warehousing. • Develop and improve our data infrastructure. • Ensure data quality, integrity, and security across all data platforms. • Optimize data systems for performance and scalability. • Troubleshoot and resolve issues related to data pipelines and data infrastructure. • Collaborate with cross-functional teams to understand data needs and deliver solutions. Minimum Qualifications • A degree in Computer Science, Statistics, Engineering, or a related quantitative field. • 3+ years of professional experience as a Data Engineer or in a similar role focused on data infrastructure. • Proficiency in Python. • Solid experience with relational databases (SQL) and NoSQL databases. • Experience with AWS and their data services. • Proven experience in building and optimizing data pipelines and data architectures. Preferred Qualifications • Experience with Mongo/Snowflake/Redis/S3 General/S3 Express. • Experience with big data technologies • Experience with Airflow. • Familiarity with containerization and orchestration tools (e.g., Docker, Kubernetes). • Experience working in a company focused on API services or search technology. • Knowledge of data governance and data security best practices.

Description Vega is one of the fastest-growing startups in cybersecurity, redefining security analytics and operations with an AI-native platform for the SOC. We are building the next-generation operating system for security teams. Vega is already delivering real impact at some of the world’s largest organizations - improving detection, unlocking the value of their security data, and reducing cost and complexity. With HQs in New York and TLV, we're looking for people who want to be a part of the next rocket-ship in cyber. We’re looking for a talented Data Engineer to join our AI team and build the data foundations that power our AI systems at scale. As a key member of the AI team, you’ll be responsible for designing, building, and operating the data layer that enables our AI models and agents to perform in production. This includes data ingestion, storage, transformation, monitoring, and defining the data strategy that ensures our AI applications receive high-quality, reliable, and timely data. We’re seeking an ambitious Data Engineer who is passionate about building robust data infrastructure, working with large-scale and complex datasets, and partnering closely with AI engineers and researchers to translate model needs into production-grade data systems. WHAT YOU WILL DO • Design, build, and operate scalable data pipelines (batch + streaming) that power Vega’s AI systems in production. • Own the end-to-end data lifecycle: ingestion, storage, transformation, serving, and continuous improvement. • Build and maintain the data layer from raw data to semantically accessible data that enables AI models and agents to perform reliably at scale. • Ensure high data quality and high-standard operation through monitoring, alerting, and validation checks. • Work with modern storage systems (data lakes, warehouses, relational, graph, and vector databases) to support diverse AI workloads. • Partner closely with AI engineers and researchers to translate model requirements into production-grade data infrastructure. • Define and evolve the data strategy to for AI applications. Requirements WHAT YOU WILL BRING • 4+ years of professional experience in data engineering or ML infrastructure roles. • Strong experience designing and building data pipelines (batch and streaming) for large-scale production systems. • Hands-on experience with data storage systems such as data lakes, data warehouses, relational databases and graph databases. • Proven ability to build reliable, observable, and scalable data infrastructure, including monitoring, alerting, and data quality checks. • Demonstrated ownership across the full data lifecycle from ingestion and modeling, to serving, monitoring, and continuous improvement. • Ability to work independently, managing priorities effectively in a fast-paced, product-driven environment, according to a dynamic data strategy. • Experience with modern data and infrastructure technologies such as DuckDB, dbt, Temporal, Trino, Spark, PostgreSQL, PGVector Neo4j, Datadog, Python, Go, Docker, and Kubernetes. • Experience working with ML models and framework as part of data pipelines (e.g. text embedding models, vector databases, semantic search algorithms) NICE TO HAVE • Experience building data infrastructure to support ML/AI systems, including feature extraction pipelines for downstream ML models and inference-time data access. • Background in working with high-volume or complex data sources such as logs, events, telemetry, or security data. • Familiarity with modern cloud platforms, preferably AWS, and cloud-native data tools. • Experience collaborating closely with ML/AI engineers to translate model and research requirements into scalable data solutions.

AppsFlyer processes 150+ billion events across its platform, and our Web Attribution team is at the center of extending that power beyond mobile. We build the product that shows advertisers which campaigns really drive results on the web. We attribute every web user journey, from first click to conversion, across thousands of apps and billions of sessions. We're looking for a Senior Data Engineer to own the technical direction of our pipelines. You'll be the team's go-to data engineering expert and a key knowledge holder: the person the team turns to for Spark, data modeling, and the hardest pipeline problems. You'll lead the team's design work and work closely with the team lead on planning and technical priorities. You'll shape the product that advertisers and marketers rely on every day. What you’ll do • Build & Own End-to-End Pipelines: Build and improve pipelines that process billions of web events (sessions, in-app events, conversions) with strict freshness and accuracy SLAs, from ingestion through distributed processing to the serving layer. • Lead Design & Architecture: Own the technical design of the team's pipelines, from spec to production. Write design docs, review the team's designs, and make the key trade-offs, such as what runs in SQL and what runs in Spark. Work with the group's architects on cross-team designs. • Drive Technical Planning: Work with the team lead on the roadmap, planning, and priorities. Break large projects into clear deliverables. Represent the team in technical discussions with Product, R&D, and partner teams. Own production incidents end-to-end and turn them into lasting fixes. What you have • 6+ years in Data / Big Data Engineering, including building and running production systems at scale. • B.Sc. in Computer Science or equivalent. • Deep, hands-on Apache Spark experience: you understand execution plans, partitioning, and memory management, and you know how to debug skew and performance problems at scale. • Deep experience with a cloud analytical warehouse (BigQuery, Snowflake, Redshift, or Databricks SQL) as both a processing and serving layer. BigQuery is a strong advantage. • A proven track record in data-system design: you've written design docs, made trade-offs between cost, latency, and correctness, and taken designs all the way to production. • Experience with workflow orchestration (e.g., Airflow) and cloud environments at production scale. GCP preferred. • Strong programming fundamentals: clean, testable, production-grade code. Scala preferred; Python for orchestration. • A natural instinct for data quality: you think about edge cases, dedup logic, and "what happens when this field is null" before anyone asks. • Hands-on use of AI tools in your daily engineering work, and a clear view of where AI helps data engineering and where it doesn't. Bonus points • Experience building or maintaining attribution / AdTech data systems. • Advanced Scala or functional programming experience. • Experience with attribution models (last-click, multi-touch, view-through). • Experience with SQL-based transformation frameworks (Dataform, dbt) or data-mesh / data-product platforms. • Experience with Kafka or streaming systems. • Experience running LLMs or ML pipelines in production. • Being introduced by an AppsFlyer team member As a global company operating from 25 offices across 19 countries, we reflect the human mosaic of the diverse and multicultural world in which we live. We ensure equal opportunities for all of our employees and promote the recruitment of diverse talents to our global teams without consideration of race, gender, culture, or sexual orientation. We value and encourage curiosity, diversity, and innovation from all our employees, customers, and partners. “As a Customer Obsessed company, we must first be Employee Obsessed. We need to make sure that we provide the team with the tools and resources they need to go All-In.” Oren Kaniel, CEO

Similarweb is the leading digital intelligence platform used by over 3500 global customers. Our wide range of solutions power the digital strategies of companies like Google, eBay, and Adidas. We help our customers succeed in today’s digital world by giving them access to data-driven insights, competitive benchmarks, strategic analysis, and more. In 2021, we went public on the New York Stock Exchange, and we haven’t stopped growing since! We’re looking for a Data Engineer with a strong applied ML focus to join our R&D department! Why is this role so important at Similarweb? Our Retail Intelligence products help leading brands and retailers understand how their products, brands and categories perform online. Behind them is data collected from retailers and marketplaces around the world: product pages, brands and categories, each described differently by every site. Your mission is to turn that data into a single, trusted view: classifying products into a unified taxonomy, normalizing brands and attributes, and matching the same entities across sources. And doing it at scale, across a catalog of more than a billion records that keeps growing and changing every day. This is an applied ML role within data engineering. You’ll build with LLMs, agentic frameworks such as LangGraph, embeddings and classical ML, and ship them as production pipelines. It’s hands-on work, not research for its own sake, but it takes a real understanding of classification and NLP methods to choose the right tool for each problem and prove that it works. So, what will you be doing all day? Your daily responsibilities may include: • Designing and building LLM-powered and ML-based pipelines that classify, normalize, structure and match product, brand and category data • Building agentic workflows (LangGraph or similar) that automate complex data tasks end to end • Choosing the right approach for each problem (LLMs, embeddings, fine-tuned models, classical classifiers or rules), balancing accuracy, cost and latency • Scaling solutions to run efficiently over billions of records, using Spark, Databricks and our cloud infrastructure • Building evaluation frameworks: ground-truth datasets, labeling processes, quality metrics and ongoing monitoring • Taking solutions from POC to production, and owning them after launch • Working closely with Product to define requirements and shape the roadmap • Collaborating with data engineers, data scientists and other R&D teams on infrastructure and best practices This is the perfect job for someone who: • Holds a B.Sc. or M.Sc. in Computer Science, Data Science, Mathematics or another relevant field • Has 4+ years of hands-on experience as a data engineer, ML engineer or data scientist, with solutions running in production • Has strong Python skills and writes production-quality code • Has hands-on experience building LLM-based applications in production (prompt engineering, structured outputs, RAG, embeddings, evaluation) • Has worked with the modern LLM stack: LLM provider APIs (OpenAI, Anthropic, etc.), LangGraph or LangChain, Hugging Face and vector stores • Has a solid grasp of text classification and NLP methods, both classical and modern, and knows when to use each • Has experience processing large-scale data with Spark/PySpark, Databricks or similar, on AWS or another cloud • Understands evaluation and data quality well: precision/recall trade-offs, building ground truth, error analysis • Is pragmatic and delivery-focused, comfortable with ambiguity, and communicates clearly with Product and business stakeholders • Has experience with taxonomies, entity resolution or product/e-commerce data (advantage) • Has experience with fine-tuning or deploying open-source models (advantage) At Similarweb, collaborating with our colleagues in-office creates a more connected, unified culture. Our best work is a product of our face-to-face collaboration, with the ability to work partially from home. Why you’ll love being a Similarwebber: You’ll actually love the product you work with: Our customers aren’t our only raving fans. When we asked our employees why they chose to come work at Similarweb, 99% of them said “the product.” Imagine how exciting your job is when you get to work with the most powerful digital intelligence platform in the world. You’ll find a home for your big ideas: We encourage an open dialogue and empower employees to bring their ideas to the table. You’ll find the resources you need to take initiative and create meaningful change within the organization. We offer competitive perks & benefits: We take your well-being seriously, and offer competitive compensation packages to all employees. We also put a strong emphasis on community, with regular team outings and happy hours. You can grow your career in any direction you choose: Interested in becoming a VP or want to transition into a different department? Whether it’s Career Week, personalized coaching, or our ongoing learning solutions, you’ll find all the tools and opportunities you need to develop your career right here. Diversity isn’t just a buzzword: People want to work in a place where they can be themselves. We strive to create a workplace that is reflective of the communities we serve, where everyone is empowered to bring their full, authentic selves to work. We are committed to inclusivity across race, gender, ethnicity, culture, sexual orientation, age, religion, spirituality, identity and experience. We believe our culture of equality and mutual respect also helps us better understand and serve our customers in a world that is becoming more global, more diverse, and more digital every day. We will handle your application and information related to your application in accordance with the Applicant Privacy Policy available here: https://www.similarweb.com/corp/legal/applicant-privacy-policies/ We will handle your application and information related to your application in accordance with the Applicant Privacy Policy available here.

At Similarweb, we're revolutionizing the way businesses interact with the digital world by revealing to them everything that happens online. Our cutting-edge platform and unique data empower over 4,300 customers globally, including industry giants like Google, eBay, and Adidas, to make game-changing decisions that drive their digital strategies. In 2021, we went public on the New York Stock Exchange, and we haven’t stopped growing since! We’re looking for a Senior Data Engineer in the Data Collection Ingest team to contribute to the design and coding of Similarweb’s data ingestion services & pipelines. This role involves working as part of a team that handles millions of requests per minute across multiple servers, and is responsible for a wide-range of data pipelines, processing billions of events each day. Why is this role so important at Similarweb? As the most trusted platform for measuring online behavior, millions of people rely on Similarweb’s insights daily as the ground truth for their knowledge of the digital world. Producing these insights requires large scale raw data to be ingested reliably in high scale to provide stable signals for analysis. As a Data Engineer you will have the opportunity to perform hands-on work and own Similarweb’s raw data ingestion pipeline end-to-end. Your work will have a direct impact on the quality and reliability of our data and the insights that our products are delivering to our customers. So, what will you be doing all day? Your role as Data Engineer of the Ingest Data Collection team means your daily responsibilities may include: • Design, code and manage end-to-end Similarweb’s data ingestion pipelines, both online and offline. • Take charge of developing & maintaining modern data infrastructure, while implementing best practices for building data pipelines. • Be responsible for high-scale ingestion services, solving challenges of availability, reliability, and scalability. • Run the production environment by monitoring availability and taking a holistic view of system health and data quality. • Own data infrastructure features from design to production using industry best practices with focus on quality and delivery. • Lead design & decision-making processes of the team. • Solve diverse complex problems of scale, performance and business logic. • Collaborate with product managers and other team leaders to plan, nurture, and implement an efficient and effective development process. • Continuously learn and evaluate new technologies in the everlasting effort to perfect our products • Perform code reviews, evaluate implementations, and provide feedback about potential improvements. • Improve your skills, learn from and mentor top-notch engineers and enrich other team members. • Have lots of fun! This is the perfect job for someone who: • Has 5+ years of experience in developing code for big data infrastructure. Proficiency in technologies such as: Databricks, Spark, Airflow, Firehose, SQS, or other similar tools. • Proven experience working with high scale on AWS or any other cloud provider. Experience in architecture and design of large-scale and high performance production systems. • Comfortable taking challenges and learning new technologies. • Excellent communication skills with the ability to provide constant dialog between teams. • Ability to take business requirements and translate them to technical alternatives by performing risk management and evaluating tradeoffs. *All Similarweb offices work in a hybrid model, so you can enjoy the flexibility of working from home with the benefits of building face to face connections with fellow Similarwebbers.* Why you’ll love being a Similarwebber: You’ll actually love the product you work with: Our customers aren’t our only raving fans. When we asked our employees why they chose to come work at Similarweb, 99% of them said “the product.” Imagine how exciting your job is when you get to work with the most powerful digital intelligence platform in the world. You’ll find a home for your big ideas: We encourage an open dialogue and empower employees to bring their ideas to the table. You’ll find the resources you need to take initiative and create meaningful change within the organization. We offer competitive perks & benefits: We take your well-being seriously, and offer competitive compensation packages to all employees. We also put a strong emphasis on community, with regular team outings and happy hours. You can grow your career in any direction you choose: Interested in becoming a VP or want to transition into a different department? Whether it’s Career Week, personalized coaching, or our ongoing learning solutions, you’ll find all the tools and opportunities you need to develop your career right here. Diversity isn’t just a buzzword: People want to work in a place where they can be themselves. We strive to create a workplace that is reflective of the communities we serve, where everyone is empowered to bring their full, authentic selves to work. We are committed to inclusivity across race, gender, ethnicity, culture, sexual orientation, age, religion, spirituality, identity and experience. We believe our culture of equality and mutual respect also helps us better understand and serve our customers in a world that is becoming more global, more diverse, and more digital every day. We will handle your application and information related to your application in accordance with the Applicant Privacy Policy available here.

At Similarweb, we're revolutionizing the way businesses interact with the digital world by revealing to them everything that happens online. Our cutting-edge platform and unique data empower over 4,300 customers globally, including industry giants like Google, eBay, and Adidas, to make game-changing decisions that drive their digital strategies. In 2021, we went public on the New York Stock Exchange, and we haven’t stopped growing since! We're seeking exceptional individuals to join us to our R&D team. At Similarweb, you'll innovate fast, collaborate with brilliant minds, solve big problems, work with cutting-edge technologies and data at incredible scales, and make a tangible impact on the world's most innovative companies. We’re looking for a Big Data Engineer to develop and integrate systems that retrieve, process and analyze data from around the digital world, generating customer-facing data. This role will report to our Team Manager, R&D. Why is this role so important at Similarweb? Similarweb is a data-focused company, and data is the heart of our business. As a big data engineer developer, you will work at the very core of the company, designing and implementing complex high scale systems to retrieve and analyze data from millions of digital users. Your role as a big data engineer will give you the opportunity to use the most cutting-edge technologies and best practices to solve complex technical problems while demonstrating technical leadership. So, what will you be doing all day? Your role as part of the R&D team means your daily responsibilities may include: • Design and implement complex high scale systems using a large variety of technologies. • You will work in a data research team alongside other data engineers, data scientists and data analysts. Together you will tackle complex data challenges and bring new solutions and algorithms to production. • Contribute and improve the existing infrastructure of code and data pipelines, constantly exploring new technologies and eliminating bottlenecks. • You will experiment with various technologies in the domain of Machine Learning and big data processing. • You will work on a monitoring infrastructure for our data pipelines to ensure smooth and reliable data ingestion and calculation. This is the perfect job for someone who: • Passionate about data. • Holds a BSc degree in Computer Science\Engineering or a related technical field of study. • Has at least 4 years of software or data engineering development experience in one or more of the following programming languages: Python, Java, or Scala. • Has strong programming skills and knowledge of Data Structures, Design Patterns and Object Oriented Programming. • Has good understanding and experience of CI/CD practices and Git. • Excellent communication skills with the ability to provide constant dialog between and within data teams. • Can easily prioritize tasks and work independently and with others. • Conveys a strong sense of ownership over the products of the team. • Is comfortable working in a fast-paced dynamic environment. Advantage: • Has experience with containerization technologies like Docker and Kubernetes. • Experience in designing and productization of complex big data pipelines. • Familiar with a cloud provider (AWS / Azure / GCP). Experience with Big Data technologies and common frameworks such as Spark, Airflow, Kafka, Parquet, Databricks, EMR, Kubernetes. About the R&D team As part of our R&D team at Similarweb, you'll have the opportunity to work on challenging algorithmic problems with no play book solution, solve problems for real customers, and work alongside the best engineers and scientists in the industry. **At Similarweb, collaborating with our colleagues in-office creates a more connected, unified culture. Our best work is a product of our face-to-face collaboration, with the ability to work partially from home.** Why you’ll love being a Similarwebber: You’ll actually love the product you work with: Our customers aren’t our only raving fans. When we asked our employees why they chose to come work at Similarweb, 99% of them said “the product.” Imagine how exciting your job is when you get to work with the most powerful digital intelligence platform in the world. You’ll find a home for your big ideas: We encourage an open dialogue and empower employees to bring their ideas to the table. You’ll find the resources you need to take initiative and create meaningful change within the organization. We offer competitive perks & benefits: We take your well-being seriously, and offer competitive compensation packages to all employees. We also put a strong emphasis on community, with regular team outings and happy hours. You can grow your career in any direction you choose: Interested in becoming a VP or want to transition into a different department? Whether it’s Career Week, personalized coaching, or our ongoing learning solutions, you’ll find all the tools and opportunities you need to develop your career right here. Diversity isn’t just a buzzword: People want to work in a place where they can be themselves. We strive to create a workplace that is reflective of the communities we serve, where everyone is empowered to bring their full, authentic selves to work. We are committed to inclusivity across race, gender, ethnicity, culture, sexual orientation, age, religion, spirituality, identity and experience. Our culture of equality and mutual respect also helps us better understand and serve our customers in a world that is becoming more global, more diverse, and more digital every day. We will handle your application and information related to your application in accordance with the Applicant Privacy Policy available here.