Top Data Engineer Jobs in Israel

Design, build, and maintain end-to-end data pipelines and models. Integrate multiple data sources, improve data quality and reliability, automate workflows, and partner with Product, Finance, Operations, and R&D to deliver trusted datasets and analytics-ready data assets.

As a Senior Software Engineer, you'll develop CrowdStrike's browser protection solutions, focusing on data protection and secure browsing experiences, collaborating on features from design to implementation.

Design, build, and maintain end-to-end ETL/ELT data pipelines and scalable data models for marketing analytics. Partner with Marketing, UA, and Monetization to enable ROAS, cohort, LTV analyses and ensure data integrity and freshness across BI reporting.

Supports the development of scalable data pipelines, data models, warehouses, semantic layers, dashboards, and analytics solutions using Python and SQL. Monitors data quality, troubleshoots workflows, documents data systems, and contributes to orchestration, testing, automation, and platform reliability. Collaborates with business and technical teams across rotating domains while exploring AI-assisted engineering and Generative AI applications. This early-career role includes mentorship, Agile participation, and increasing project ownership.

Lead architecture and schema design for a new data product, build full-stack production features, design and optimize data pipelines, integrate complex systems, manage cost and performance, mentor engineers, and collaborate with cross-functional teams to deliver scalable data solutions.

Build and operate Nebius’s data platform for search quality, ML pipelines, product analytics, and business operations. Responsibilities include developing batch and streaming pipelines, evolving warehouse models, improving observability and data quality, supporting production incident resolution and backfills, and partnering cross-functionally to deliver trustworthy datasets. The role covers ingestion, medallion-layer warehousing, consumer datasets, dashboards, governance, testing, documentation, deployment, and architectural standards across large-scale, multi-region systems.

Seeking a Python Data Engineer to build and manage ETLs, process large datasets with Spark/Hadoop, maintain Airflow pipelines, write SQL, and collaborate closely with the team to deliver data solutions for cyber challenges.

Own the architecture and delivery of web-scale data ingestion pipelines, including resilient web scraping, transformation, storage, distributed cloud systems, data quality, APIs, and workflow monitoring. The role requires expertise in Airflow, Databricks, anti-bot scraping, scalable system design, AI coding assistants, and connecting pipeline decisions to business value. This position is based four days per week in Tastewise’s Tel Aviv office.

Design, build, and maintain scalable data warehouse infrastructure and pipelines. Enable analytics and product teams via data modeling, BI dashboards, data governance, and quality monitoring.

Design, build, and maintain data management systems and ETL pipelines, ensuring data quality and collaborating with teams for optimal solutions.

Lead Interconnect Cluster Performance efforts using big data and failure analysis to ensure high-quality product deliveries. Drive cross-functional collaborations (Process, Mechanical, Hardware, Thermal), lead task forces, design and improve test plans, manage field and lab failure analysis, and partner with Customer Support, Marketing, Engineering, Quality, and Reliability to improve product performance and customer satisfaction.

As a Backend/Data Engineer, you'll design scalable data solutions, optimize performance, and maintain data pipelines while ensuring data quality.

Seeking a Data Engineer with over 4 years of experience to build and optimize data platforms, work on data pipelines, and collaborate across teams to enhance data solutions and architecture.

The Data Engineer will manage data architecture and pipelines, ensuring reliability and performance for product and AI decisions. Responsibilities include optimizing data processing, maintaining security, and integrating new data sources.

Build and maintain scalable cloud-based data pipelines and ETL processes using Python, SQL, AWS, Airflow, Databricks, and Spark. Design data models, optimize large-scale workloads, integrate APIs and databases, and monitor pipeline reliability. Develop AI agents with LangGraph and related frameworks that connect tools and data sources and automate user workflows. Collaborate with BI analysts and stakeholders to define data requirements and resolve data issues.

Designs, develops, deploys, and optimizes large-scale data pipelines across cloud and on-premise environments. Ingests high-volume data, analyzes datasets with Data Scientists, and builds data solutions for data warehouse and AI projects. The role requires Python, Spark, dbt, pipeline orchestration, container platforms, advanced data formats, AWS data services, and BI tool integration, along with strong analytical, collaborative, and independent working skills.

Design, develop, and maintain ETL/ELT pipelines, troubleshoot queries, implement data governance, and stay updated on data engineering technologies.

Build and own data pipelines and infrastructure that convert simulation and real-robot recordings into versioned, training-ready datasets for humanoid robotics, handling extraction, transformation, storage formats, curation, and traceability.

The Backend Infrastructure & Data Engineer will design, build, and maintain scalable data systems, manage cloud infrastructure, and develop efficient data pipelines for a fast-paced Web3 security startup.

Design, build, and maintain scalable ETL/ELT data pipelines and data warehouse solutions. Integrate and model data from multiple sources, ensure data quality and monitoring, and support production deployments. Develop and operationalize AI/ML and LLM-powered data solutions, collaborate with global stakeholders, and provide production support and anomaly detection capabilities.

The role involves designing and implementing data processing pipelines, optimizing performance, and collaborating with cross-functional teams to enhance security analytics.

The role involves designing and developing data protection extensions for macOS, troubleshooting issues, and collaborating with teams across locations.

Design and build scalable data pipelines and models that normalize and correlate security data for Torq's AI-SOC context graph. Collaborate with product and stakeholders to run end-to-end POCs, profile and validate datasets, integrate identity/endpoint/security sources, and deliver production-ready dbt-backed models. Measure coverage and accuracy, and iterate on data models to enable autonomous security decisions.

The Data Engineer will create and maintain data pipelines, implement high-scale systems, collaborate with engineers and data scientists, and leverage AI/ML technologies to fulfill customer requirements.

The Senior Backend Data Engineer will design and maintain data pipelines and infrastructure, support AI/ML product development, and ensure data quality. Collaborating with cross-functional teams is essential to deliver scalable solutions and improve outcomes for clinicians and clients.