Full Time Remote friendly

Data Platform Tech Lead

Check Point Hybrid - Tel Aviv, Israel (Hybrid)
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Role snapshot

Compensation N/A
Location Hybrid - Tel Aviv, Israel (Hybrid) Work from anywhere

Technologies

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Job description

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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