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.

Own and evolve end-to-end analytics foundations: design data models, pipelines, and BI layers; collaborate with Data Science and business stakeholders; ensure data quality, performance, and trusted metrics; use GenAI to speed analytics engineering; mentor and set standards across the company.

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.

The Data Engineer will design and develop data solutions for clients, build data pipelines, lakes, DWHs, and implement AI/ML models.

Design, build, and operate production Snowflake data pipelines and models (ingestion, CDC, transformation, validation). Create analytics-ready, governed datasets and semantic models for BI and enterprise AI, enforce security/governance and FinOps, and partner with stakeholders on certified metrics, lineage, and delivery.

The Data Engineer will design and maintain data pipelines, develop data platforms, ensure data quality, and troubleshoot issues.

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.

Design and improve ML-driven data curation pipelines for large autonomous-vehicle datasets: embedding extraction, VLM scene analysis, scoring, deduplication, sampling, GPU inference at scale, validation/diagnostics, dataset SDK and 3D geometry tooling, and collaborate with algorithm and infra teams to close data gaps.

Build and improve ML-driven data curation pipelines for large-scale autonomous-vehicle datasets: embedding extraction, scene detection, GPU inference orchestration, scoring, deduplication, sampling, dataset validation, SDK/tools, and collaboration with algorithm and infra teams to ensure balanced, high-quality training data.

Build and improve ML-driven data curation pipelines for autonomous-vehicle datasets: run GPU inference at scale, extract embeddings, score/deduplicate/sample data, ensure rare scenarios are represented, validate dataset quality, and contribute to dataset SDKs and 3D geometry tooling while collaborating with algorithm and infra teams.

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.

As a Software & Data Engineer at Via, you will design and build scalable data pipelines, manage data models, and ensure data quality to improve public transportation systems.

As an AI Data Engineer, you will design and implement data pipelines for the Large Market Model (LMM), focusing on feature engineering, system reliability, and driving innovation through advanced AI technologies.

The AI Data Engineer will architect and engineer data pipelines for the Large Market Model (LMM), ensuring system reliability and exploring innovative features in AI-driven solutions.

Design, build, and maintain scalable ETL/data pipelines and storage for large datasets. Collaborate with product, data science, and analysts to ensure data quality, integrity, and low-latency performance. Implement monitoring, validation, and cost-efficient solutions, recommend new tools, and leverage AI assistants to improve productivity and pipeline development.

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.

Design, build, and scale a BI data platform and ETL/ELT pipelines (batch and real-time). Own data ingestion, transformation, modeling, storage, observability, lineage, and governance. Integrate tools like Airflow, Databricks, streaming platforms, and BI tools. Collaborate with engineers, analysts, and product managers to enable analytics, reporting, and operational product integrations.

Build and maintain end-to-end ETL pipelines and billing data infrastructure using Big Data tools. Improve pipeline scalability and performance, analyze and extend business logic, collaborate across teams, and mentor peers while evaluating and adopting new technologies.

The Full-Cycle Data Engineer will design and deploy data pipelines, build dashboards, ensure data quality, and translate product-related queries into metrics and insights, collaborating across teams to enhance data analytics.

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.

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

The Senior Data Engineer will build and own the ClickHouse analytics platform, lead data migrations, optimize queries, and ensure ingest reliability while educating the team.

The Data Engineer will build and optimize data pipelines, develop reliable data models, integrate new data sources, and ensure data quality while collaborating with analysts and data scientists.

Lead end-to-end data and automation solutions for Clinical Research: intake, business case development, design, build, validation, deployment and lifecycle management of ETL pipelines, dashboards, workflow automation and AI-assisted processes. Ensure compliance (ICH GCP), measure impact via KPIs, manage stakeholders and change, and scale reusable solutions across countries and region.