Senior Data Engineer

Company Description Arrakis Security provides total visibility, policy enforcement, and real-time remediation for autonomous AI agents operating within enterprise infrastructure. The company focuses on securing complex, AI-driven environments where traditional security tools are not sufficient. By monitoring agent behavior and enforcing policies in real time, Arrakis Security helps organizations reduce risk and maintain compliance. Working with Arrakis Security offers the opportunity to shape the future of AI security and protect mission-critical systems at scale. Role Description This is a full-time Senior Data Engineer role based in the Tel Aviv District, Israel, with a hybrid work model that allows a combination of on-site and work-from-home days. The Senior Data Engineer will design, build, and maintain scalable data pipelines to support monitoring, analytics, and policy enforcement for autonomous AI agents. Day-to-day responsibilities include implementing robust ETL processes, developing and optimizing data models, and managing data warehousing solutions that enable reliable, high-performance access to security and operational data. The role involves collaborating closely with product, data science, and security teams to define data requirements, ensure data quality, and deliver datasets and tools that power analytics, detection, and real-time remediation. The Senior Data Engineer will also contribute to architectural decisions, performance tuning, and best practices for data governance and documentation. Qualifications

• Strong skills in Data Engineering, including building and maintaining scalable data pipelines and distributed data systems.

• Demonstrated experience with Data Modeling and Data Warehousing to support analytics, reporting, and high-volume data workloads.

• Hands-on proficiency with Extract Transform Load (ETL) processes and tools for integrating data from multiple sources.

• Ability to apply Data Analytics concepts to support decision-making, security insights, and product features.

• Proficiency in programming languages commonly used for data engineering (such as Python, Scala, or Java) and SQL.

• Experience with modern data platforms and technologies (for example, cloud data services, streaming frameworks, or big data ecosystems).

• Background in security, AI, or monitoring systems is an advantage, as well as experience working in fast-paced startup environments.

• Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, or a related field, or equivalent practical experience.

• Ability to work effectively in a hybrid environment, collaborate with cross-functional teams, and communicate clearly in English.