Check Point Software Technologies

Cybersecurity software licenses and security appliances

Data Platform Tech Lead

Data EngineeringConfirmed live in the last 24 hours

Full-timeTel Aviv-Yafo, IsraelNo salary listed

About the Job

Requirements

At least 6 years of hands-on Data Engineering experience building and operating production-scale pipelines.
Proven experience building and maintaining a large-scale Data Lake.
Deep, hands-on experience with Spark, including tuning, partitioning, and debugging large jobs.
Strong Python skills and advanced SQL skills.
Backend development experience with REST APIs, microservices, and 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, including testing, CI/CD, code quality, and performance profiling.
Ability to take problems from design to production with little guidance and suggest improvements independently.

Responsibilities

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 the Data Lake/Lakehouse, including data modeling, partitioning, and storage formats.
Write production-grade backend services and REST APIs that expose data platform capabilities.
Build data quality, observability, and monitoring into the platform, and own pipelines end to end in production.
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.

Desired Qualifications

Hands-on Databricks experience.
Experience with Azure data services or EventHub.
Experience with streaming frameworks and real-time processing, such as Spark Structured Streaming, Kafka, or Flink.
Experience with table formats such as Delta Lake or Iceberg.
Background in cybersecurity, SaaS, or large-scale enterprise environments.
Experience with data governance, observability, or self-service platforms.

Job Description

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

Qualifications

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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Additional Information

About the Company

Check Point Software Technologies

Cybersecurity software licenses and security appliances

Check Point Software Technologies provides cybersecurity solutions for networks, cloud, and mobile environments. Its Infinity platform unifies threat prevention with centralized security management across on-premises, cloud, and remote access, while Quantum, CloudGuard, and Harmony cover network, cloud, and remote-user security respectively. Revenue comes from subscription-based software licenses, security appliances, and support, with additional training and certification programs for professionals. The goal is to deliver integrated protection across environments with simplified management and recurring revenue from subscriptions.

Company size: 5,001-10,000
Company stage: IPO
Headquarters: Tel Aviv-Yafo, Israel
Founded: 1993

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