Big Data Engineer

A high-growth Israeli cybersecurity startup is developing an innovative defense platform designed to secure enterprise SaaS applications. Operating with a high-caliber team of approximately 100 professionals, the company provides organizations with deep visibility and real-time protection across their distributed cloud software environments.

The engineering culture is centered on building robust, high-scale data infrastructures to support sophisticated threat detection and risk mitigation.

The company is located in Central Israel (prime location near major transport hubs) and operates a hybrid work model with one day remote flexibility.

Role Overview:

• Infrastructure Architecture: Joining a core engineering team to design, build, and scale the company’s foundational Data Infrastructure.
• Data Pipeline Engineering: Developing high-throughput streaming and batch processing pipelines using Python, Spark, and Kafka.
• Cloud Data Management: Implementing and optimizing Data Lake and Warehouse solutions within an AWS environment (utilizing Athena, Glue, and Airflow).
• Modeling & Transformation: Leveraging DBT and SQL to create structured, performant data models that power security analytics and reporting.
• Technical Ownership: Taking responsibility for the end-to-end data lifecycle, ensuring data reliability, integrity, and accessibility for R&D and product teams.

Requirements:

• 5+ years of professional experience as a Data Engineer – Mandatory.
• Proven track record in building Data Infrastructures from the ground up – Mandatory.
• Deep experience with Data Lake or Data Warehouse (DWH) architectures – Mandatory.
• Extensive hands-on experience with Cloud-native data services (specifically AWS) – Mandatory.
• Strong proficiency in Python and SQL for complex data manipulation.
• Familiarity with modern data orchestration and transformation tools (e.g., Airflow, DBT, Spark).