Data Platform Tech Lead
Check Point Software Technologies · Tel Aviv · Israel · hybrid
We'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.
- Design, build, and maintain large-scale batch and streaming data pipelines (ETL/ELT) across multiple products
- Develop and optimize Spark workloads for performance, cost, and reliability on large data volumes
- Build and evolve our Data Lake / Lakehouse, including data modeling, partitioning, and storage formats
- Write production-grade backend services and REST APIs that expose data platform capabilities
- Build in data quality, observability, and monitoring from the start, and own your pipelines in production end to end
- Automate and improve the data platform, including AI-assisted development and LLM-powered data workflows
- Work closely with R&D and product teams, and contribute to design and code reviews
- 6+ years of hands-on Data Engineering experience building and operating production-scale pipelines
- Proven experience with building and maintaining a large scale Data Lake
- Deep, hands-on experience with Spark (tuning, partitioning, debugging large jobs)
- Strong Python and advanced SQL
- Backend development experience: REST APIs, microservices, service design patterns
- Broad database experience across relational, analytical/columnar, NoSQL, and streaming stores
- Experience with cloud-based data platforms
- Practical experience with AI tools and agents, such as integrating or orchestrating LLM-powered workflows in production
- Strong engineering fundamentals: testing, CI/CD, code quality, and performance profiling
- Self-directed: you take a problem from design to production with little guidance and suggest improvements without being asked
Nice to have
- Hands-on Databricks experience is a major advantage
- Azure data services or EventHub
- Streaming frameworks and real-time processing (e.g., Spark Structured Streaming, Kafka, Flink)
- Table formats such as Delta Lake or Iceberg
- Background in cyber security, SaaS, or large-scale enterprise environments
- Experience with data governance, observability, or self-service platforms
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