Data Engineer jobs in Ramat Gan

Join one of Israel's leading insurance and financial companies as a Data Engineer on the core data team, building end-to-end Data solutions on a modern cloud stack. You'll work at the center of an enterprise-scale data landscape - Databricks, Spark, and Azure - with direct impact on BI, AI, and analytics capabilities across the business. What You'll Do: Develop and implement data pipelines and ETL/ELT processes, both Batch and Streaming. Build Data Products and enterprise-wide data solutions on Databricks, Spark, and Azure. Implement Data Quality, Monitoring, and CI/CD practices across data workflows. Work directly with business stakeholders and the BI, AI, and analytics teams. Own solutions from the characterization phase through to production. Requirements: 2+ years of experience as a Data Engineer - Must Strong hands-on experience with SQL and Python - Must Experience working with Databricks and Spark - Must Experience developing ETL/ELT processes in a Cloud environment - Must Experience working with Data Lake and Data Warehouse environments - Must Familiarity with Git, CI/CD, and DataOps practices - Must Ability to independently lead technical tasks and projects - Must Experience working in Enterprise environments - Advantage Familiarity with Data Governance and Data Quality practices - Advantage Experience supporting AI and Analytics projects - Advantage

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/.

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

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!

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!