Top Data Engineer Jobs in Jerusalem

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.

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

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.

Build and maintain complex ETL pipelines and backend BI/data solutions using SSIS, Airflow, dbt and Snowflake. Work with high-scale databases, design implementations, and collaborate with stakeholders across the company.

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.

Own and evolve ClickHouse's Python connector and SDK ecosystem; build enterprise-grade integrations with orchestration and transformation tools; design AI/LLM integration patterns for RAG, vector search, and feature pipelines; engage with open-source community; collaborate with Product and Cloud teams to prioritize and deliver robust, high-performance connectors.

Design, build, and operate scalable data platform infrastructure, including high-volume batch and streaming ingestion, data lake architecture, Kubernetes-based processing with KEDA, Terraform IaC, data orchestration (Airflow/Prefect), Snowflake usage, and performance tuning to support analytics and AI workloads.

Own and scale AWS OpenSearch infrastructure and PostgreSQL-to-OpenSearch pipelines. Design indices, mappings, analyzers, and retention policies. Optimize queries and bulk indexing, monitor cluster health, implement retries/idempotency, backfills, reconciliation, and disaster recovery. Build dashboards, alerts, runbooks, and participate in incident response while collaborating with backend, DB, infra, and product teams.

Design and implement high-performance, low-latency runtime enforcement for data access across databases and sensitive data. Build proxies, orchestrators, and production-grade runtime components; ensure high availability, observability, and safe upgrades. Participate in design tradeoffs across security, performance, scalability, and operability while collaborating with product, platform, and security teams.

Design and implement core YTsaurus functionality in C++, build and evolve platform-level capabilities, improve APIs and UX for internal users, own production quality including incident response/on-call, and collaborate with stakeholders to prioritize and deliver scalable data platform features.

The Staff Data Engineer will design and maintain data models, pipelines, and ETLs, ensuring data correctness and collaboration with cross-functional teams to meet business needs.

Build and maintain high-performance, fault-tolerant distributed backend services and data pipelines for large genomic and health datasets. Design storage, indexing, and async event workflows; optimize latency, throughput, and reliability. Partner with bioinformatics and product teams to validate scientific accuracy and guard AI-driven responses.

The Senior Data Engineer will design, build, and maintain data infrastructure for analyzing large datasets, focusing on data management, ETL processes, and collaboration with stakeholders to align data projects with business objectives.

Own, operate, and scale real-time data platforms (Kafka, Elasticsearch). Build automation, IaC, monitoring, internal tools and self-service APIs. Troubleshoot production incidents, run RCA, perform capacity planning, and collaborate with engineers and analysts to ensure reliable data delivery.