Data Engineer jobs in Israel

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.

Description Deloitte’s the leading and largest consulting firm in the world, is looking for a Data Engineer to join our Data and AI Practice. We are building cutting-edge data solutions that introduce next level automations and aim for low-code/no-code data platforms that allows our customers to deliver fast while hiding all the engineering complexities behind. If you are not afraid of any engineering task, likes to build cool stuff and enjoy when customers use your craft – you belong with us. Requirements • Proven experience with Big Data projects and in depth knowledge with GCP BigQuery. Certifications are desired • Experience building cloud-scalable, real-time and high-performance Data Solutions of 3+ years. • Programming Skills with Spark, Python. • Solid engineering foundations (good coding practices, good architectural design skills). • Proven experience with building data pipelines, preferably with Airflow/Composer, Dataform/DBT, Spark, Dataplex • Solid cloud development experience in GCP (and/or others). Certifications are desired • Advanced SQL knowledge and capabilities • Big Advantage – Experience with Databricks • Experience or knowledge in AI/GenAI/ML/MLOps/LLM - advantage • Team player, positive, likes to dream big and fulfill dreams all at the same time • Experience and/or ability to work with AI tools – mandatory Location: Tel Aviv, Hybrid. We at Deloitte believe that diversity and inclusion among our people is a critical component of our success, which is why we cultivate an organizational culture that embraces diversity in all its forms.

Description This is a great opportunity to be part of one of the fastest-growing infrastructure companies in history, an organization that is in the center of the hurricane being created by the revolution in artificial intelligence. "VAST's data management vision is the future of the market."- Forbes VAST Data is the data platform company for the AI era. We are building the enterprise software infrastructure to capture, catalog, refine, enrich, and protect massive datasets and make them available for real-time data analysis and AI training and inference. Designed from the ground up to make AI simple to deploy and manage, VAST takes the cost and complexity out of deploying enterprise and AI infrastructure across data center, edge, and cloud. Our success has been built through intense innovation, a customer-first mentality and a team of fearless VASTronauts who leverage their skills & experiences to make real market impact. This is an opportunity to be a key contributor at a pivotal time in our company’s growth and at a pivotal point in computing history. We are seeking an experienced Solutions Data Engineer who possess both technical depth and strong interpersonal skills to partner with internal and external teams to develop scalable, flexible, and cutting-edge solutions. Solutions Engineers collaborate with operations and business development to help craft solutions to meet customer business problems. A Solutions Engineer works to balance various aspects of the project, from safety to design. Additionally, a Solutions Engineer researches advanced technology regarding best practices in the field and seek to find cost-effective solutions. Job Description: We’re looking for a Solutions Engineer with deep experience in Big Data technologies, real-time data pipelines, and scalable infrastructure—someone who’s been delivering critical systems under pressure, and knows what it takes to bring complex data architectures to life. This isn’t just about checking boxes on tech stacks—it’s about solving real-world data problems, collaborating with smart people, and building robust, future-proof solutions. In this role, you’ll partner closely with engineering, product, and customers to design and deliver high-impact systems that move, transform, and serve data at scale. You’ll help customers architect pipelines that are not only performant and cost-efficient but also easy to operate and evolve. We want someone who’s comfortable switching hats between low-level debugging, high-level architecture, and communicating clearly with stakeholders of all technical levels. Key Responsibilities: • Build distributed data pipelines using technologies like Kafka, Spark (batch & streaming), Python, Trino, Airflow, and S3-compatible data lakes—designed for scale, modularity, and seamless integration across real-time and batch workloads. • Design, deploy, and troubleshoot hybrid cloud/on-prem environments using Terraform, Docker, Kubernetes, and CI/CD automation tools. • Implement event-driven and serverless workflows with precise control over latency, throughput, and fault tolerance trade-offs. • Create technical guides, architecture docs, and demo pipelines to support onboarding, evangelize best practices, and accelerate adoption across engineering, product, and customer-facing teams. • Integrate data validation, observability tools, and governance directly into the pipeline lifecycle. • Own end-to-end platform lifecycle: ingestion → transformation → storage (Parquet/ORC on S3) → compute layer (Trino/Spark). • Benchmark and tune storage backends (S3/NFS/SMB) and compute layers for throughput, latency, and scalability using production datasets. • Work cross-functionally with R&D to push performance limits across interactive, streaming, and ML-ready analytics workloads. • Operate and debug object store–backed data lake infrastructure, enabling schema-on-read access, high-throughput ingestion, advanced searching strategies, and performance tuning for large-scale workloads. Required Skills & Experience: • 2–4 years in software / solution or infrastructure engineering, with 2–4 years focused on building / maintaining large-scale data pipelines / storage & database solutions. • Proficiency in Trino, Spark (Structured Streaming & batch) and solid working knowledge of Apache Kafka. • Coding background in Python (must-have); familiarity with Bash and scripting tools is a plus. • Deep understanding of data storage architectures including SQL, NoSQL, and HDFS. • Solid grasp of DevOps practices, including containerization (Docker), orchestration (Kubernetes), and infrastructure provisioning (Terraform). • Experience with distributed systems, stream processing, and event-driven architecture. • Hands-on familiarity with benchmarking and performance profiling for storage systems, databases, and analytics engines. • Excellent communication skills—you’ll be expected to explain your thinking clearly, guide customer conversations, and collaborate across engineering and product teams.

Description DRS RADA is a leading defense high-tech company specializing in radar systems development. We are seeking an experienced Data Engineer to join our data engineering team. In this role, you will play a crucial part in designing, developing, and maintaining scalable data pipelines and infrastructure to support our AI department. This is an opportunity to work with cutting-edge technologies in a fast-paced production environment, driving impactful, data-driven solutions for the business. Key Responsibilities: • Design, develop, and optimize ETL/ELT pipelines for large-scale data processing. • Work with a modern data stack, including Databricks (Spark, SQL), Apache Airflow, and Azure services. • Troubleshoot and optimize queries and jobs for performance improvements. • Implement best practices for data governance, security, and monitoring. • Stay updated with industry trends and emerging technologies in data engineering. If you're passionate about building scalable data solutions and thrive in a fast-paced environment, we’d love to hear from you! Requirements • 4 years of experience in data engineering or related fields. • Proficiency in Python for data processing and automation (mandatory). • Deep understanding of Apache Spark and Databricks for big data processing (mandatory). • Experience with Git (mandatory). • Expertise in Apache Airflow for workflow orchestration. • Familiarity with cloud-based environments, particularly Azure. • Advanced proficiency in SQL and query optimization. • Familiarity with data modeling, ETL/ELT principles, and performance tuning. • Knowledge of CI/CD and containerization (Docker). • An enthusiastic, fast-learning, team-oriented, and motivated individual who loves working with data.

The AI Engineering group builds modern infrastructure and solutions that improve how algorithms are developed at Mobileye. We are a small, independent team of experienced engineers with a mix of skills in algorithms, software, and infrastructure. We work in a DevOps style and build cross-team solutions that support research and development of advanced perception algorithms. Our flagship project is a unified AV dataset used to train and evaluate next-generation models. We take large volumes of multi-camera video, object labels, HD maps, and sensor data from across the organization, and turn it into a curated, high-quality training set - at scale. We are looking for someone who brings ML and computer-vision depth to the team - someone who can help shape the intelligence layer that decides what data is worth training on. What will your job look like: • Work collaboratively with shared ownership. Your focus area will be the curation and ML side of our data pipeline, but you will contribute across the full stack alongside the rest of the team. • Build and improve the curation pipeline - from vision-model embeddings and scene detection, through VLM-based scene analysis, to scoring, deduplication, and sampling that produces a balanced and diverse dataset. • Run and optimize GPU inference at scale (embedding extraction, VLM inference) across thousands of driving sessions using workflow orchestration. • Develop scoring and sampling strategies that ensure rare but important scenarios (night driving, adverse weather, hazardous situations) are well-represented in the final dataset. • Work with algorithm teams to understand what data gaps hurt model performance and translate those into curation criteria. • Build validation and diagnostics that measure dataset quality - not just pipeline health, but whether the data is actually good for training. • Contribute to the core dataset SDK, converter, and 3D-geometry tooling (camera projection, calibration, coordinate transforms). All you need is: • 4+ years in data engineering or backend/software engineering with serious data work — pipelines that run in production, not just notebooks. • Strong Python and the PyData stack (NumPy, PyArrow, Pandas, DuckDB). • Some background in research, algorithms, or ML — enough that you can read a paper, understand a model's outputs, and have informed conversations with algorithm engineers. • Comfort working with vision-model outputs as data: embeddings, detection results, VLM responses. • Ability to work across team boundaries — this role lives between algorithm teams, infra teams, and our own. Nice to have: • Experience with autonomous-driving datasets or perception pipelines. • 3D geometry and camera model intuition (or the mathematical background to ramp up). • Workflow orchestration (Argo, Airflow, Kubeflow). • Vector databases or columnar analytics (LanceDB, DuckDB, Parquet at scale). • Familiarity with curation concepts (active learning, hard-example mining, distribution balancing) — useful context, not a requirement. • Exposure to LLM agents or agentic workflows for data tasks.

Join PUMA, the team developing the deep-learning perceptions solutions at the heart of Mobileye's autonomous-driving system. Our work powers advanced, large-scale multi-task models. We are looking for an ML Data Engineer to own the engineering foundations behind its development and training. You will build pipelines and tools that process images, video, geometric information, and evaluate model outputs. Working alongside deep-learning researchers, you will eliminate resource-intensive bottlenecks and reduce computation costs and iteration time. What will your job look like? • Optimize distributed data and evaluation pipelines for memory efficiency, throughput, and training performance. • Build tools for data exploration, manipulation, validation, and quality assessment. • Own model manipulation, packaging, distribution workflows, and interfaces with downstream deployment and EyeQ integration. • Coordinate data contracts and workflows with researchers, infrastructure and data teams, and internal customers across Mobileye. All you need is: • Bachelor's degree in Computer Science, Software Engineering, Electrical Engineering, or a related field from a leading university. • 4+ years of hands-on software or data-engineering experience. • Excellent Python and Linux skills with strong software-engineering foundations. • Experience with SQL, Spark, and PyArrow. • Experience optimizing distributed pipelines or compute-intensive systems for memory use and parallel execution. • Familiarity with PyTorch and ML workflows, including datasets, training, checkpoints, evaluation, and GPU computation. • Strong ownership, independent problem-solving, and cross-team collaboration skills. Nice to have: • Master's degree in a relevant field. • Experience in computer vision or autonomous-driving systems. • Familiarity with model deployment, hardware-aware ML, or specialized AI accelerators. Mobileye changes the way we drive, from preventing accidents to semi and fully autonomous vehicles. If you are an excellent, bright, hands-on person with a passion to make a difference come to lead the revolution!

The AI Engineering group builds modern infrastructure and solutions that improve how algorithms are developed at Mobileye. We are a small, independent team of experienced engineers with a mix of skills in algorithms, software, and infrastructure. We work in a DevOps style and build cross-team solutions that support research and development of advanced perception algorithms. Our flagship project is a unified AV dataset used to train and evaluate next-generation models. We take large volumes of multi-camera video, object labels, HD maps, and sensor data from across the organization, and turn it into a curated, high-quality training set - at scale. We are looking for someone who brings ML and computer-vision depth to the team - someone who can help shape the intelligence layer that decides what data is worth training on. What will your job look like: • Work collaboratively with shared ownership. Your focus area will be the curation and ML side of our data pipeline, but you will contribute across the full stack alongside the rest of the team. • Build and improve the curation pipeline - from vision-model embeddings and scene detection, through VLM-based scene analysis, to scoring, deduplication, and sampling that produces a balanced and diverse dataset. • Run and optimize GPU inference at scale (embedding extraction, VLM inference) across thousands of driving sessions using workflow orchestration. • Develop scoring and sampling strategies that ensure rare but important scenarios (night driving, adverse weather, hazardous situations) are well-represented in the final dataset. • Work with algorithm teams to understand what data gaps hurt model performance and translate those into curation criteria. • Build validation and diagnostics that measure dataset quality - not just pipeline health, but whether the data is actually good for training. • Contribute to the core dataset SDK, converter, and 3D-geometry tooling (camera projection, calibration, coordinate transforms). All you need is: • 4+ years in data engineering or backend/software engineering with serious data work — pipelines that run in production, not just notebooks. • Strong Python and the PyData stack (NumPy, PyArrow, Pandas, DuckDB). • Some background in research, algorithms, or ML — enough that you can read a paper, understand a model's outputs, and have informed conversations with algorithm engineers. • Comfort working with vision-model outputs as data: embeddings, detection results, VLM responses. • Ability to work across team boundaries — this role lives between algorithm teams, infra teams, and our own. Nice to have: • Experience with autonomous-driving datasets or perception pipelines. • 3D geometry and camera model intuition (or the mathematical background to ramp up). • Workflow orchestration (Argo, Airflow, Kubeflow). • Vector databases or columnar analytics (LanceDB, DuckDB, Parquet at scale). • Familiarity with curation concepts (active learning, hard-example mining, distribution balancing) — useful context, not a requirement. • Exposure to LLM agents or agentic workflows for data tasks. Mobileye changes the way we drive, from preventing accidents to semi and fully autonomous vehicles. If you are an excellent, bright, hands-on person with a passion to make a difference come to lead the revolution!

About Nebius: Nebius is leading a new era in cloud infrastructure for the global AI economy. We are building a full-stack AI cloud platform that supports developers and enterprises from data and model training through to production deployment, without the cost and complexity of building large in-house AI/ML infrastructure. Built by engineers, for engineers. From large-scale GPU orchestration to inference optimization, we own the hard problems across compute, storage, networking and applied AI. Listed on Nasdaq (NBIS) and headquartered in Amsterdam, we have a global footprint with R&D hubs across Europe, the UK, North America and Israel. Our team of 1,500+ includes hundreds of engineers with deep expertise across hardware, software and AI R&D. The role The Data Engineering team builds and operates the data platform that powers analytics, business intelligence, operational reporting, and data-driven products across Nebius. We ingest data from internal and external systems, develop reliable transformation pipelines and data models, and make trusted datasets available to business and product teams. We are looking for a Senior Data Engineer to own substantial parts of our data platform and deliver complex data products end to end. You will turn ambiguous business needs into pragmatic technical solutions, make architecture and implementation trade-offs, and improve the reliability, scalability, and usability of our data ecosystem. You will work closely with product, platform, and business teams, helping them use data effectively while ensuring that our systems remain maintainable and trustworthy as Nebius grows. Your responsibilities: • Own the design, delivery, and operation of complex data pipelines, datasets, and platform components. • Translate business and analytical requirements into scalable data models, reliable data products, and clear technical plans. • Design and evolve data architecture, storage, processing, and orchestration patterns for large-scale workloads. • Improve data quality, observability, lineage, and incident response for critical datasets and pipelines. • Investigate and resolve challenging performance, reliability, and data-correctness issues in production. • Establish reusable tools, conventions, and automation that improve engineering productivity and reduce operational risk. • Work with product teams and business stakeholders to define data contracts, priorities, and success criteria. • Contribute to technical direction through design reviews, thoughtful trade-offs, and documentation. • Support and mentor other engineers through reviews, pairing, and knowledge sharing. • Participate in the on-call rotation and take ownership of improving the operational health of the systems you support. Must-haves: • 5+ years of experience in data engineering, backend engineering, or a related role; or equivalent experience delivering and operating production data systems. • Proven experience independently delivering complex data pipelines or data-platform capabilities from problem definition through production operation. • Strong Python and SQL skills, including writing maintainable production code and optimizing non-trivial queries. • Hands-on experience with workflow orchestration tools such as Airflow, Prefect, or Dagster. • Strong understanding of data modeling, including designing maintainable analytical models and data contracts for multiple consumers. • Solid knowledge of data architectures and storage systems, including the trade-offs between different processing and storage approaches. • Experience designing for reliability: testing, monitoring, data-quality validation, alerting, debugging, and incident resolution. • Ability to make technical decisions under ambiguity, explain trade-offs clearly, and collaborate effectively with engineers and non-technical stakeholder Nice-to-haves: • Experience with real-time or event-driven data platforms and streaming technologies. • Experience building or operating cloud-native services with Docker and Kubernetes. • Familiarity with Infrastructure as Code, particularly Terraform. • Experience with data governance, access control, privacy, and compliance requirements such as GDPR or SOC 2. • Experience with data observability and quality tools or frameworks, such as Great Expectations. • Experience improving engineering standards through shared libraries, platform tooling, technical documentation, or mentoring. We conduct coding interviews as part of the process. Benefits & Perks: • Competitive compensation • Career growth and learning opportunities • Flexibility and ownership • Collaborative and innovative culture • Opportunity to work on impactful AI projects • International environment and talented teams What's it like to work at Nebius: Fast moving - Bold thinking - Constant growth - Meaningful impact - Trust and real ownership - Opportunity to shape the future of AI Equal Opportunity Statement: Nebius is an equal opportunity employer. We are committed to fostering an inclusive and diverse workplace and to providing equal employment opportunities in all aspects of employment. We do not discriminate on the basis of race, color, religion, sex (including pregnancy), national origin, ancestry, age, disability, genetic information, marital status, veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by applicable law. Applicants must be authorized to work in the country in which they apply and will be required to provide proof of employment eligibility as a condition of hire. If you need accommodations during the application process, please let us know.

About Nebius: Nebius is leading a new era in cloud infrastructure for the global AI economy. We are building a full-stack AI cloud platform that supports developers and enterprises from data and model training through to production deployment, without the cost and complexity of building large in-house AI/ML infrastructure. Built by engineers, for engineers. From large-scale GPU orchestration to inference optimization, we own the hard problems across compute, storage, networking and applied AI. Listed on Nasdaq (NBIS) and headquartered in Amsterdam, we have a global footprint with R&D hubs across Europe, the UK, North America and Israel. Our team of 1,500+ includes hundreds of engineers with deep expertise across hardware, software and AI R&D. The role Nebius is looking for a Senior Data Engineer who in addition to building and owning data pipelines will also drive the design and technical leadership within the data engineering team. This is a hands-on data engineering role, focused on designing, implementing, and maintaining reliable data flows for analytics and machine learning. Infrastructure, cloud, and Kubernetes are used only as tools to run pipelines reliably and cost-efficiently — this is not an SRE or platform engineering role. You’re welcome to work in our offices in Tel Aviv, Israel. Your responsibilities will include: Core Responsibilities (Primary Focus) • Design, build, and own production-grade data pipelines using Python and SQL. • Develop stateless, idempotent pipelines that are resilient to retries, failures, and infrastructure interruptions. • Implement data transformations, validation, and data quality checks. • Optimize pipelines for performance, reliability, and cost efficiency. • Collaborate closely with Analytics, Data Science, and ML teams to deliver trusted datasets. Supporting Infrastructure (Secondary Focus) • Orchestrate pipelines using a workflow orchestration framework (e.g., Airflow or equivalent). • Package and run data workloads using Docker and deploy them on Kubernetes. • Use autoscaling and Spot / Preemptible compute for efficient pipeline execution. • Build CI/CD automation for data pipelines. • Use Infrastructure as Code only to provision and manage the infrastructure required to run pipelines. We expect you to have: • 8+ years of experience as a Data Engineer, primarily focused on building data pipelines. • 6+ years of hands-on experience with Python and SQL. • 3+ years of experience running workloads on Kubernetes. • Strong understanding of stateless system design and idempotent data processing. • Experience building and operating data pipelines in cloud environments. • Experience with workflow orchestration frameworks. • Strong Linux fundamentals and production debugging skills. • Working knowledge of spoken and written English It will be an added bonus if you have: • Experience contributing to or working extensively with open-source software. • Experience building data pipelines using Apache Spark or similar distributed processing frameworks. • Experience building data pipelines that support machine learning workflows. • Familiarity with cost-optimized data processing (e.g., Spot / Preemptible compute). • Experience with relational and non-relational data stores. • Experience working with large-scale or high-reliability data systems. • Experience collaborating with strong Data Science and ML teams. Benefits & Perks: • Competitive compensation • Career growth and learning opportunities • Flexibility and ownership • Collaborative and innovative culture • Opportunity to work on impactful AI projects • International environment and talented teams What's it like to work at Nebius: Fast moving - Bold thinking - Constant growth - Meaningful impact - Trust and real ownership - Opportunity to shape the future of AI Equal Opportunity Statement: Nebius is an equal opportunity employer. We are committed to fostering an inclusive and diverse workplace and to providing equal employment opportunities in all aspects of employment. We do not discriminate on the basis of race, color, religion, sex (including pregnancy), national origin, ancestry, age, disability, genetic information, marital status, veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by applicable law. Applicants must be authorized to work in the country in which they apply and will be required to provide proof of employment eligibility as a condition of hire. If you need accommodations during the application process, please let us know.

Who Connecteam is: Connecteam is the leading platform for managing deskless teams, trusted by over 80,000 businesses worldwide. We built Connecteam for real operators - the people running shifts, jobs, and teams across stores and sites. The kind of work that doesn’t happen behind a desk, and doesn’t have time for messy spreadsheets, scattered group chats, or tools that don’t talk to each other. Connecteam brings daily operations and team communication into one intuitive app - from hiring and scheduling to training, tasks, and day-to-day coordination. It gives teams the clarity and control to run the day, shift after shift, job after job. Backed by $220M+ from Insight Partners, Stripes, and Tiger Global, Connecteam is rapidly expanding worldwide - empowering frontline teams to work smarter, stay connected, and operate with greater efficiency. About the role: We are looking for an experienced and hands-on Backend Engineer to be a key player in building high-scale Data Platforms and Products for our business teams. This role involves working with large datasets and scalable systems, and developing internal tools to enable data-driven decision-making across the company. The team builds the backend systems and data infrastructure the rest of the company relies on: internal products, APIs, event pipelines, and integrations with external tools. The data comes from the full product, at the volume of over 1.7 million daily active users. The features are multi-system: an API, a pipeline, and often LLM-backed flows that have to stay correct in production. LLMs and agents are part of the job. We use them to write, review, and debug code, and we ship them inside the product: agents and LLM features that other teams depend on. Key Responsibilities: • Develop internal tools and products for teams across Connecteam. • Build and maintain services and APIs that support complex, multi-step workflows. • Operate in a real-time, event-driven environment at high volume. • Create and manage data pipelines, including the checks that keep data trustworthy. • Design and ship LLM and agent features: tool use, prompts, evaluation, and the limits around cost, latency, and quality. • Use coding agents as part of normal delivery, and raise the quality of what they produce. • Take ownership of multiple systems and products. • Work in a multi-cloud environment (Azure/GCP/AWS). • Integrate third-party tools with our platform. • Translate ambiguous business requirements into a technical plan and lead it through to production. Our Tech Stack: • Python, FastAPI, Tornado, SQLAlchemy, Pydantic, MySQL, MongoDB, Redis, BigQuery, RabbitMQ, Kafka, Google Pub/Sub, Airflow, Airbyte, Kubernetes, Prometheus, Grafana, React, TypeScript, LLMs and agent frameworks. Experience & Skills: • Experience: Minimum 8 years as a Backend Engineer. • Proficiency in Python: at least 8 years, or deep backend experience and a fast ramp onto Python. • Proven experience writing and maintaining services and REST APIs in production, at a scale where volume and failure handling matter. • SQL Expertise: Strong proficiency in SQL. • Event-Driven Development: Hands-on experience with event-driven development. • Daily use of LLMs and coding agents in how you build. • Big Data Experience: Familiarity with big data and high-velocity/volume systems is a plus. • Cloud Environments: Experience with multi-cloud environments (Azure, GCP, AWS). #LI-Hybrid Joining Connecteam Is The Smart Move: • We build our people up. Every team member is treated as a long-term investment and we recognize the value in always nurturing and training them so they can go above and beyond in their skills and job duties. • We make an impact on our customer’s business. We are on a mission to provide managers of all business types and sizes with the tools they need to communicate, operate, engage, and run their deskless workforce. Our product offers them an effective and affordable solution to run their business. • We get the job done. Connecteam employees are passionate in executing their job duties so they can drive the company forward and provide real value to our customers. • We have fun! From weekly happy hours to holiday parties, we always enjoy each other’s company (and good food, of course). Connecteam is like one big, happy family! • Everyone is welcome. Connecteam is committed to building an encouraging, caring, and supportive environment. We share a responsibility to support our team and enrich their lives. Together we will shape the future of work! Our privacy policy

About Aidoc Aidoc is the market leader in healthcare AI and has developed the world's largest clinical frontier model, supporting nearly 50 million patients each year. Aidoc is deployed in more than 2,000 medical centers worldwide. Since our founding in 2016, Aidoc has raised over $500 million and achieved a record number of FDA-cleared solutions. Medical diagnosis is hitting a breaking point, where the number of physicians hasn't kept up with the rapidly growing patient load. This leads to misdiagnosis and treatment delays that result in hundreds of thousands of deaths every year. Aidoc assists clinicians by precisely highlighting diseases directly on medical images, preventing misdiagnosis and ensuring that urgent patients receive the immediate attention they need. About this role The Data-Nexus team, a central part of the R&D department at Aidoc, is seeking a versatile Senior Data Engineer to take part in leading Aidoc’s data vision using a lake-house architecture, and building high-scale solutions for handling and consuming the different data assets of the company. In this role you’ll go beyond traditional boundaries, taking on full product responsibilities - from conceptualization and architecture to design, maintenance, and continuous development. You will collaborate closely with stakeholders across the company to ensure our solutions effectively meet their needs. The ideal candidate will have strong data engineering capabilities, along with software development skills including understanding of designing and managing AWS cloud infrastructure and strong knowledge of different data architectures, methods and tools. Responsibilities • Design and development of scalable, reliable, and secure data infrastructure and build ETL pipelines that handle diverse clinical data for research. Write production SQL, Spark jobs and craft schemas that evolve gracefully as research and production questions change. • Automate releases with CI/CD and Infrastructure as Code. • Optimise throughput, latency and cloud cost to meet research timelines at large scale. • Develop and maintain high-quality, scalable, and efficient code while fostering a culture of continuous improvement through regular retrospectives and knowledge sharing. • Take ownership of the full development lifecycle, including requirement gathering, design, implementation, testing, deployment, and ongoing maintenance. • Collaborate with cross-functional teams, including data scientists, data analysts, product managers, regulatory teams, and other developers, to drive the development of new tools and features that support Aidoc's mission. • Explore and adopt new technologies and frameworks that can enhance the capabilities of the Data-Nexus team and the overall data projects in Aidoc. Requirements • BSc/MSc in Computer Science, Engineering, or a related field. • 8+ years building data or backend systems in Python or a similar coding language, with a strong focus on cloud data infrastructure and scalable systems. • Strong command of SQL and a track record of pragmatic schema design. • Deep understanding of data modelling, ETLs and streaming technologies, including hands-on experience with tools like big-data tools like AWS Kinesis / Kafka, Spark. • Familiarity with modern lakehouse / warehouse tech, like Databricks, Delta Lake, Iceberg, Snowflake, Redshift. • Strong understanding of distributed systems, microservices architecture, containerization, and CI/CD pipelines. • Proficiency in Infrastructure as Code (IaC) tools, like Terraform or AWS CDK. • Experience with containerization and orchestration tools - Docker, Kubernetes (K8s). • Ability to take full product ownership from ideation to delivery, ensuring alignment with business objectives. • Familiarity with agile development methodologies. • Excellent communication skills with the ability to work effectively across teams and a customer-oriented mindset. Clear English communication is required. • Advantages: • Deep expertise in Databricks (Delta Lake, Unity Catalog, DLT). • Knowledge of the medical tech world, including EHR (HL7, FHIR) data and imaging data. • Prior work in regulated domains (healthcare, fintech, aviation), experience with enforcing and managing compliance requirements like HIPAA or FedRAMP. Working at Aidoc Our Perks: • Be part of something big - using cutting-edge technologies to transform the Healthcare industry (while saving patients’ lives) • We work in a hybrid model, with our new offices located at 34 HaMasger Street in Tel Aviv and parking for employees. • Amazing and healthy breakfasts and lunches prepared daily by our personal chef! • Stocked up kitchen & meal card • Wellness: Aidoc employees-only gym, plus Pilates, Yoga, and functional workouts classes. • Amazing culture - collaborative, transparent & fun! • Attractive compensation package & benefits Aidoc is deeply committed to creating an inclusive workplace, and to the principle of equal opportunity for all individuals. We prohibit discrimination and harassment based on race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, veteran status, or any other status protected by law.

Our Mission At Palo Alto Networks®, we’re united by a shared mission—to protect our digital way of life. We thrive at the intersection of innovation and impact, solving real-world problems with cutting-edge technology and bold thinking. Here, everyone has a voice, and every idea counts. If you’re ready to do the most meaningful work of your career alongside people who are just as passionate as you are, you’re in the right place. Who We Are In order to be the cybersecurity partner of choice, we must trailblaze the path and shape the future of our industry. This is something our employees work at each day and is defined by our values: Disruption, Collaboration, Execution, Integrity, and Inclusion. We weave AI into the fabric of everything we do and use it to augment the impact every individual can have. If you are passionate about solving real-world problems and ideating beside the best and the brightest, we invite you to join us! We believe collaboration thrives in person. That’s why most of our teams work from the office full time, with flexibility when it’s needed. This model supports real-time problem-solving, stronger relationships, and the kind of precision that drives great outcomes. Job Summary IDIRA by Palo Alto Networks seeks an experienced Senior Staff Data Engineer to join our AI and Data Solutions unit and champion an AI-first strategy. You will spearhead the development of Data Lakehouse processes, model core product domains, and define data engineering best practices across the organization. Serving as a technical project lead, you will provide strong direction and collaborate with Data Science, Analytics, R&D, and IT teams to elevate onboarding workflows. This role demands a proactive approach to optimizing system capabilities and driving cross-functional data initiatives. Key Responsibilities • Own the design, implementation, and optimization of scalable Data Lakehouse and Data Warehouse architectures across diverse cloud ecosystems. • Spearhead the development of robust ETL/ELT pipelines and data ingestion processes utilizing SQL, Python, PySpark, and DBT. • Apply advanced data modelling techniques to structure complex data assets into optimized facts, dimensions, and partitions. • Partner with cross-functional leadership across data science, analytics, R&D, and IT to identify requirements and improve workflows. • Orchestrate complex data workflows combining tools like Airflow and DBT with advanced Gen-AI development workflows using CloudCode. • Define, document, and popularize data engineering best practices, design patterns, and data quality standards across the unit. • Evaluate and implement modern data technologies spanning vendor-specific and open-source landscapes including GCP, AWS, and Apache Iceberg. • Provide technical direction and hands-on guidance to ensure high-performance execution, reliable pipeline delivery, and proactive problem-solving. Qualifications Required Qualifications • 5+ years of experience with advanced data modeling techniques and concepts (e.g., Facts, Dimensions, Partitions). • 5+ years of experience designing and implementing end-to-end data ingestion and ETL processes within Data Lakehouse architectures. • 5+ years of hands-on experience programming in SQL and Python, PySpark, Java, or Scala. • Demonstrated experience leading technical projects, driving stakeholder alignment, and navigating cross-functional dynamics. • Proven experience working within cloud environments (AWS or GCP), with a strong requirement for AWS. • Deep understanding of the modern data landscape and open-source tools (e.g., Iceberg, DBT, Airflow). • Proven capability in using and orchestrating Gen-AI workflows based on CloudCode and Cursor. Preferred Qualifications • Deep expertise in the AWS ecosystem, including Glue, Athena, SageMaker, and EMR. • Advanced experience with Data Warehouse technologies, especially Apache Iceberg or BigQuery. • Leadership or mentorship experience within a data engineering or analytics unit. • Background or domain knowledge in cybersecurity is a strong advantage. Our Commitment We’re trailblazers that dream big, take risks, and challenge cybersecurity’s status quo. It’s simple: we can’t accomplish our mission without diverse teams innovating, together. We are committed to providing reasonable accommodations for all qualified individuals with a disability. If you require assistance or accommodation due to a disability or special need, please contact us at [email protected]. Palo Alto Networks is an equal opportunity employer. We celebrate diversity in our workplace, and all qualified applicants will receive consideration for employment without regard to age, ancestry, color, family or medical care leave, gender identity or expression, genetic information, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran status, race, religion, sex (including pregnancy), sexual orientation, or other legally protected characteristics. All your information will be kept confidential according to EEO guidelines. Is role eligible for Immigration Sponsorship? No. Please note that we will not sponsor applicants for work visas for this position.

Our Mission At Palo Alto Networks®, we’re united by a shared mission—to protect our digital way of life. We thrive at the intersection of innovation and impact, solving real-world problems with cutting-edge technology and bold thinking. Here, everyone has a voice, and every idea counts. If you’re ready to do the most meaningful work of your career alongside people who are just as passionate as you are, you’re in the right place. Who We Are In order to be the cybersecurity partner of choice, we must trailblaze the path and shape the future of our industry. This is something our employees work at each day and is defined by our values: Disruption, Collaboration, Execution, Integrity, and Inclusion. We weave AI into the fabric of everything we do and use it to augment the impact every individual can have. If you are passionate about solving real-world problems and ideating beside the best and the brightest, we invite you to join us! We believe collaboration thrives in person. That’s why most of our teams work from the office full time, with flexibility when it’s needed. This model supports real-time problem-solving, stronger relationships, and the kind of precision that drives great outcomes. Job Summary Join the Cortex team as a Principal Backend Engineer and own the backend strategy for our integrated detection and response engine. You will be responsible for transforming raw endpoint, network, and cloud data into actionable intelligence, using AI-driven techniques to dramatically reduce false positives and focus our defense on what truly matters: stopping the world’s most critical threats. Key Responsibilities • backed by the massive scale and resources of a global leader, to architect and scale a world-class data infrastructure capable of processing billions of events per second in real-time. • Integrate state-of-the-art AI technologies to transform raw telemetry from the industry's leading cyber products into high-fidelity, actionable intelligence. • Own the end-to-end software development life cycle, from conceptualizing complex distributed systems to deploying high-performance code, building AI-augmented systems that are fast, maintainable, and resilient. Qualifications • 8+ years of software engineering experience. • Experience in distributed cloud products. • Knowledge of the cyber field. • BSc in Computer Science or equivalent knowledge or equivalent military experience. Preferred Qualifications • Experience with a variety of database technologies (e.g., MySQL, Cassandra, Google BigQuery, Amazon Redshift, Elasticsearch, Neo4J). • Experience in designing, building, and maintaining a scalable server-side application. • Proven experience in AI Workloads, including hands-on experience building and scaling AI/ML workloads, and familiarity with LLM orchestration and Model Serving. • Experience in Python. • Experience with Google Cloud Platform (GCP). • Experience with Kubernetes or Docker. Our Commitment We’re trailblazers that dream big, take risks, and challenge cybersecurity’s status quo. It’s simple: we can’t accomplish our mission without diverse teams innovating, together. We are committed to providing reasonable accommodations for all qualified individuals with a disability. If you require assistance or accommodation due to a disability or special need, please contact us at [email protected]. Palo Alto Networks is an equal opportunity employer. We celebrate diversity in our workplace, and all qualified applicants will receive consideration for employment without regard to age, ancestry, color, family or medical care leave, gender identity or expression, genetic information, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran status, race, religion, sex (including pregnancy), sexual orientation, or other legally protected characteristics. All your information will be kept confidential according to EEO guidelines. Is role eligible for Immigration Sponsorship? No. Please note that we will not sponsor applicants for work visas for this position.

Description We Are KPMG Israel. KPMG Israel is more than a professional services firm, we are a community of people driven by impact. As part of a leading global network, we partner with the most influential organizations to drive large-scale business and technology transformation, combining strategic thinking, innovation, and advanced technologies. Guided by integrity, excellence, and forward thinking, we help organizations navigate complexity and create real change. Our people are at the center, with space to lead, experiment, and grow in a dynamic and collaborative environment that connects personal development with meaningful impact on the future of business and society. We are seeking a skilled and motivated Data Engineer with expertise in Elasticsearch, cloud technologies, and Kafka. As a data engineer, you will be responsible for designing, building and maintaining scalable and efficient data pipelines that will support our organization's data processing needs. The role will entail: • Design and develop data platforms based on Elasticsearch, Databricks, and Kafka • Build and maintain data pipelines that are efficient, reliable and scalable • Collaborate with cross-functional teams to identify data requirements and design solutions that meet those requirements • Write efficient and optimized code that can handle large volumes of data • Implement data quality checks to ensure accuracy and completeness of the data • Troubleshoot and resolve data pipeline issues in a timely manner Requirements • Bachelor's or Master's degree in Computer Science, Engineering, or a related field • 3+ years of experience in data engineering • Expertise in Elasticsearch, cloud technologies (such as AWS, Azure, or GCP), Kafka and Databricks • Proficiency in programming languages such as Python, Java, or Scala • Experience with distributed systems, data warehousing and ETL processes • Experience with Container environment such AKS\EKS\OpenShift is a plus • high security clearance is a plus The position is open for all genders as well as people with disabilities.

Description Commit Data is looking for a highly skilled Data Engineer to join our growing Data Analytics Department. As a Data Engineer in a multi cloud company, you will build data-driven solutions for our customers using cutting-edge data tools and large-scale data on AWS\GCP\Azure. Job Responsibilities: • Lead data solutions design and development for our various clients and projects. • Design the solution by understanding the needs, modeling the data, choosing the right tools and defining the interfaces/dashboards. • Develop Data Pipelines, Data Lakes, DWHs, AI\ML models, Dashboards and reports using advanced tools and leading technologies. Requirements • Requirements: • 5+ years of relevant experience as Data Engineer – a must. • Experience with Python based data pipelines/ETLs and other ETL\ELT tools (such as Glue, Rivery, Data Factory, DBT). • High Proficiency in SQL – a must. • Experience designing and developing DWHs in the cloud – Redshift\Snowflake\BigQuery is a must. • Experience with BI & visualizations tools like Tableau\Quicksight\Power BI\Looker. • Knowledge and experience with AI\ML (working with tools like SageMaker\ Bedrock\ Q\ BigQuery ML\ Vertex AI\ Gemini) - big advantage. • Strong analytical and problem-solving skills with attention to details. • High self-learning skills • Fluent English

Job Description • Architect and evolve our Data Warehouse, Data Lake, and ETL/ELT pipelines across multiple products and business domains • Design and build enterprise-grade backend services and APIs that expose data platform capabilities at scale • Own technical decisions on scalability, reliability, observability, and data quality • Lead cross-functional initiatives with R&D, product, analysts, and business stakeholders • Mentor data engineers and developers through design reviews, technical leadership, and engineering best practices • Drive adoption of modern data technologies, AI-first practices, and automation Qualifications • 6+ years in Data Engineering, including production-scale platform design and operation using Spark • 2+ years as a Tech Lead or senior engineer leading technical initiatives • Hands-on backend development experience - REST/gRPC APIs, microservices, service design patterns - at enterprise scale • Broad database fluency: relational, analytical, NoSQL, columnar, and streaming stores • Advanced SQL and strong Python; proven experience building and optimizing large-scale ETL/ELT pipelines • Experience with cloud-based data platforms and AI-driven data workflows • Practical proficiency with AI agents and tools - building, integrating, or orchestrating LLM-powered workflows in production environments • Strong communication skills with technical and non-technical stakeholders • Self-directed and forward-thinking - you bring a clear point of view, drive initiatives without being told, and see around corners on where the platform needs to go next Nice to have • Azure data services, Databricks or EventHub • Streaming and real-time data processing architectures • Background in cyber security, SaaS, or large-scale enterprise environments • Data governance, observability, or self-service platform experience #LI-NK2

Description CodeValue is looking for an experienced, hands-on Senior Backend Engineer with strong expertise in Python and data-intensive systems to join our development team. In this role, you will design, develop, and maintain backend services and reliable data pipelines, build integrations with external systems, and work with modern cloud technologies and AI-powered development tools. You will collaborate closely with engineering, data, and implementation teams to deliver scalable, high-quality software solutions. Key Responsibilities • Design, develop, and maintain backend services and production-grade data pipelines. • Build and operate batch and event-driven ETL processes, including data transformation, validation, and schema management. • Design and maintain data models and schemas that serve as a reliable source of truth across systems. • Develop integrations with external systems and data sources, including API-based integrations and structured data files. • Build reusable integration frameworks and tools to streamline data onboarding, validation, and troubleshooting. • Work with relational and document databases, ensuring data consistency, reliability, and performance. • Implement monitoring, logging, alerting, and observability for production systems. • Ensure data security, auditability, and appropriate access controls in compliance-sensitive environments. • Collaborate with backend, DevOps, data, and other cross-functional teams throughout the software development lifecycle. • Leverage AI-assisted development tools to improve engineering productivity and code quality. Requirements • 5+ years of hands-on experience in backend software development, with significant experience building data pipelines or data-intensive systems. • Strong proficiency in Python, including asynchronous programming and modern web frameworks such as FastAPI. • Proven experience designing, developing, and maintaining production data pipelines, including batch and event-driven ETL. • Hands-on experience with AWS services such as S3, SQS, Lambda, RDS/PostgreSQL, and DynamoDB. • Experience deploying and maintaining containerized services in Kubernetes environments. • Strong SQL skills and practical experience with relational and document databases. • Experience with Python data-processing tools such as pandas and Parquet, as well as schema validation libraries such as Pydantic. • Experience owning production systems end to end, including monitoring, alerting, troubleshooting, and incident handling. • Experience using AI-powered coding tools such as Claude Code or Cursor as part of the daily development workflow. • Experience working in Agile development environments. • Bachelor's or Master's degree in Computer Science or a related field. • Strong analytical and problem-solving skills, a data-oriented mindset, and a proactive approach to delivery. • Excellent written and verbal English communication skills. Advantages • Experience working with healthcare data standards and integrations, such as HL7v2, FHIR, Epic, or Oracle Health. • Experience integrating workforce management or scheduling platforms, such as UKG or QGenda. • Familiarity with handling sensitive data and security frameworks such as HIPAA or SOC 2. • Experience building multi-tenant SaaS platforms. • Experience with data governance, audit logging, and tenant isolation.

Realize your potential by joining the leading performance-driven advertising company! As a Staff Engineer - Data Platform on the infrastructure department in ourTel Aviv Office, you’ll play a vital role in as a Staff Engineer – Data Platform in the Infrastructure Department in our Tel Aviv office, you’ll play a vital role in building the core data platform that powers Taboola’s reporting, billing, ML training, experimentation, revenue optimization, and business decision-making — ensuring data is reliable, fresh, scalable, and easy to use. You’ll be a senior technical leader across the Data Platform group, owning the hardest technical challenges across Spark, Iceberg, Kafka, and StarRocks. As a hands-on individual contributor, you’ll drive technical excellence and make every engineer around you better through mentoring and technical leadership. 1.4 billion users. 950,000 requests per second. 150TB of fresh data every day. 800M metrics every minute. That's the scale Taboola's Data Platform group operates at. To thrive in this role, you'll need: • 10+ years of hands-on software engineering, with deep expertise in Java or an equivalent JVM/object-oriented language • Deep, hands-on expertise in Apache Spark — internals, Spark SQL and the Catalyst optimizer, and performance and cost tuning at scale • Production experience with Apache Iceberg (or another open table format such as Delta Lake or Hudi) — table design, partitioning, compaction, and metadata/catalog management • Deep expertise in Apache Kafka — internals, partitioning and delivery semantics, and operating high-throughput pipelines in production • Hands-on experience with StarRocks or a similar MPP/real-time analytics engine (Druid, ClickHouse, Trino) • Lead by example with AI: introduce agent-based engineering workflows, measure their impact, and help the group adopt them • A track record of designing, building, and owning large-scale distributed data systems end to end — from architecture to production reliability • Proven experience mentoring engineers and growing technical leaders — through design reviews, code reviews, pairing, and knowledge sharing • Ability to influence without authority and drive alignment across teams, managers, and stakeholders • Highly proficient with Linux and Kubernetes in production • B.Sc. in Computer Science or equivalent experience Bonus points if you have: • Contributions to open-source data projects (Spark, Iceberg, Kafka, StarRocks, or similar) • Conference talks, blog posts, or other public technical writing • Experience running Spark on GPU (RAPIDS) or other query acceleration techniques • Experience with stream processing (Spark Structured Streaming, Kafka Streams, Flink) • Experience with dbt and/or Airflow • Knowledge of Ansible, Puppet, or similar configuration systems • A track record of leveraging AI agents to accelerate engineering work • Familiarity with how ML training pipelines consume data, to partner effectively with algo teams How you’ll make an impact: • Shape the technical direction of the Data Platform group — the architecture, the long-term roadmap, and the bets we make on emerging tech (Iceberg, StarRocks, GPU Spark, dbt, AI tooling) • Mentor and grow engineers across the group: lead design reviews, pair on hard problems, review code with care, and help strong engineers grow into technical leaders • Raise the engineering bar group-wide — set standards for design, code quality, testing, observability, and operational excellence • Own the hardest problems on our stack: Spark performance and cost across 60,000+ jobs/day, Iceberg table management at Taboola scale, high-throughput Kafka ingestion, and low-latency analytics on StarRocks • Evolve our Spark SQL platform and the core framework code used across R&D — making the call on what gets built, refactored, or retired • Drive the evolution of our lakehouse, with Iceberg as the backbone — from ingestion through storage, compaction, and serving • Be the go-to expert for the production health of the main Taboola data pipeline — the system behind reports, ML model training, billing, and other business-critical processes — and lead deep-dives and postmortems on the toughest incidents • Partner with team leaders, group managers, and fellow principal engineers to shape how the platform evolves across R&D, balancing the needs of algo, product, finance, and infrastructure stakeholders • Stay deeply hands-on — write production code, build prototypes, and prove out new technology before the group commits to it • Represent the group internally and externally — in architecture forums, hiring, open-source communities, and conference talks • Directly shape how billions of people discover the internet Here are some of the things engineers in our group have done — or are doing right now • Pioneered deployment of Spark SQL workloads on GPU with RAPIDS • Delivered a real-time pipeline reports product serving all our customers on top of Druid • Actively migrating a proprietary ETL system to dbt-core • Pioneered usage of Iceberg (and gave conference talks about it) — yes, we manage it ourselves • Productionizing our StarRocks deployments • Building pipelines on top of Spark Streaming, Iceberg, and dbt • Extending data solutions to help algo engineers iterate fasterOur Tech Stack Java, Spark, Kafka, Iceberg, Hadoop, Cassandra, Vertica, StarRocks, MySQL, HDFS, BigQuery, Docker, Linux, Kubernetes, Prometheus, Grafana, Airflow, dbt, Druid Why Taboola? If you ask Taboolars what they love about working here, they’ll tell you that they’ve been empowered to realize their full potential while growing and learning from and with smart and talented people. They’ll also share more about: • Adam Singolda, Taboola Founder and CEO says; “You can copy anything from another business but you can’t copy a company’s culture.” • Well-being: Competitive benefits and well-being programs tailored to the region, including comprehensive health benefits, a fully stocked kitchen, and location-specific perks. • Flexibility: We offer a hybrid work schedule with 3 days in-office with an option to come in more often if desired. • Work with some of the biggest names: Our publisher partners include Yahoo, Conde Nast, Fox Sports, NBCU, ESPN, CBS, and E! Online. Our advertiser clients include Wells Fargo, Honda, Pinterest, and Expedia. Ready to realize your potential? Taboola is an equal opportunity employer and we value diversity in all forms. We are committed to creating an inclusive environment for all employees and believe such an environment is critical for success. Employment is decided on the basis of qualifications, merit, and business need. Learn more about #TaboolaLife on LinkedIn, Instagram, X, & the Taboola Life Blog. About Taboola Taboola empowers businesses to grow through performance advertising technology that goes beyond search and social and delivers measurable outcomes at scale. Taboola works with thousands of businesses who advertise directly on Realize, Taboola’s powerful ad platform, reaching approximately 600M daily active users across some of the best publishers in the world. Publishers like NBC News, Yahoo, and OEMs such as Samsung, Xiaomi and others use Taboola’s technology to grow audience and revenue, enabling Realize to offer unique data, specialized algorithms, and unmatched scale. #LI-ID #LI-Hybrid