Top Data Engineer Jobs in Israel

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

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.

Design, develop, test, maintain, and debug user-space embedded applications at low and system levels. Participate in architecture definition, design reviews, test planning, and software integration. Collaborate with software, integration, systems, support, and hardware teams while keeping current with IoT technologies and development tools.

Develop embedded software and control systems for high-performance power electronics in data centers. Responsibilities include designing, optimizing, testing, and maintaining real-time firmware across multiprocessor platforms; developing on microcontrollers; owning products from simulation through field deployment; and integrating software with hardware. The role requires expertise in C/C++, power conversion topologies, control algorithms, RTOS or bare-metal programming, embedded interfaces, and firmware debugging.

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.

Own the design, delivery, and operation of complex data pipelines, datasets, and platform components. Translate business needs into scalable data models and reliable data products, improve data quality and observability, resolve production issues, and establish reusable engineering tools and standards. Collaborate with product and business stakeholders, contribute to architecture decisions, mentor engineers, and participate in on-call support.

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

Develop and maintain backend data capabilities, ETL processes, and production data pipelines in a GCP environment. Collaborate with product and frontend teams, contribute to roadmap and backlog planning, implement and maintain features, review code, reduce technical debt, and provide engineering feedback. The role requires Python, Spark, PySpark, big-data technologies, Terraform, CI/CD, and strong communication and problem-solving skills.

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.

Build and maintain Trigo's analytics data stack: design analytics-ready data models, own the BI semantic layer, ensure data quality and observability, collaborate with stakeholders to translate business questions into scalable data solutions, and support ad-hoc analyses.

As a Data Engineer, you will design and maintain data pipelines, develop APIs, integrate LLMs and ML models, and optimize performance for scalability and reliability.

Design, build, and maintain scalable data pipelines, ETL processes, and data infrastructure. Optimize storage and retrieval for structured and unstructured data, integrate data solutions with products, apply DevOps practices (CI/CD, IaC, observability), and use AWS and ElasticSearch. Maintain SQL and NoSQL databases and leverage containerization (Docker, Kubernetes).

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

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

Work on Attribute's backend data platform: co-own roadmap, design and implement ETL and data pipelines, review code, maintain codebase health, and operate production SaaS cloud services while collaborating with product and frontend teams.

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 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.

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.

Test and approve ETL processes, database scripts, and data pipelines for accuracy, integrity, performance, and reliability. Build automated testing scripts and simulations, apply BDD methodologies, create test documentation and feature files, troubleshoot defects, perform root cause analysis, and support production maintenance. Collaborate with development and data teams to improve testing processes and data quality.

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.

Design, build, and maintain scalable pipelines for heterogeneous biological, genomic, single-cell, and clinical data. Enhance data warehouse capabilities, productize scientific algorithms, and develop AI-native data infrastructure. Establish governance for data quality, security, and privacy; collaborate with data scientists and AI/ML engineers; mentor engineers in AI-assisted development; and maintain technical documentation.

Design, develop, and maintain scalable big data pipelines and cloud infrastructure for a location analytics platform. Ensure data quality through validation, cleansing, and enrichment; optimize distributed processing and storage performance; implement governance and privacy practices; monitor and troubleshoot pipeline health; collaborate with analysts, data scientists, product managers, and engineers; and mentor junior data engineers.

Build and manage scalable data lakes, warehouses, ETL pipelines, and orchestrated ingestion and transformation workflows. Develop data models, optimize SQL queries, support streaming and high-volume architectures, and implement data security, governance, quality, compliance, and lineage. The role requires ownership of architecture and code quality while using AI-assisted development tools to deliver complex multi-file implementations.