Data Platform Tech Lead

Data Platform Tech LeadFull-timeReferral Category: Standard PositionCP Department: Products - R&DOffice Location: Tel-AvivCareer site Category: R&DCompany DescriptionWe're looking for a Tech Lead who is more than a great data engineer - someone who brings equal depth in backend software engineering and broad fluency across data technologies, databases, and large-scale distributed systems. You'll own the architecture and hands-on development of our data platform while driving engineering excellence across the team.Job DescriptionDesign, build, and maintain large-scale batch and streaming data pipelines (ETL/ELT) across multiple productsDevelop and optimize Spark workloads for performance, cost, and reliability on large data volumesBuild and evolve our Data Lake / Lakehouse, including data modeling, partitioning, and storage formatsWrite production-grade backend services and REST APIs that expose data platform capabilitiesBuild in data quality, observability, and monitoring from the start, and own your pipelines in production end to endAutomate and improve the data platform, including AI-assisted development and LLM-powered data workflowsWork closely with R&D and product teams, and contribute to design and code reviewsQualifications6+ years of hands-on Data Engineering experience building and operating production-scale pipelinesProven experience with building and maintaining a large scale Data LakeDeep, hands-on experience with Spark (tuning, partitioning, debugging large jobs)Strong Python and advanced SQLBackend development experience: REST APIs, microservices, service design patternsBroad database experience across relational, analytical/columnar, NoSQL, and streaming storesExperience with cloud-based data platformsPractical experience with AI tools and agents, such as integrating or orchestrating LLM-powered workflows in productionStrong engineering fundamentals: testing, CI/CD, code quality, and performance profilingSelf-directed: you take a problem from design to production with little guidance and suggest improvements without being askedNice to haveHands-on Databricks experience is a major advantageAzure data services or EventHubStreaming frameworks and real-time processing (e.g., Spark Structured Streaming, Kafka, Flink)Table formats such as Delta Lake or IcebergBackground in cyber security, SaaS, or large-scale enterprise environmentsExperience with data governance, observability, or self-service platforms#LI-NK2By clicking the link above or any third-party link within this posting, you are leaving this site and going to a third-party website where the third-party website's terms and privacy policy applyI'm interestedI'm interestedPrivacy NoticeImprint