Autonomy for the world. Backed by a16z.
About the role
Shield AI is seeking a Data Engineer to build the reliable, governed data foundation for Finance's next generation of planning and decision support. Working on our Databricks platform, you will own reusable integrations, semantic-layer infrastructure, and production data services that support analytics and AI-enabled applications. You will combine engineering rigor with AI-assisted development to increase delivery speed, reliability, and cost efficiency. Found on 1752vc Careers, the job board for startup and VC roles.
What they're looking for
- Hands-on production data engineering experience with SQL and Python or PySpark
- Experience with cloud data platforms, orchestration, data modeling, and governed serving patterns
- Ability to design for observability, recoverability, security, and maintainability
- Proficiency with AI coding assistants and independent validation of generated work
- Practical experience enabling AI capabilities on enterprise data, ideally in Databricks, adjacent Snowflake Cortex or comparable experience is welcome
- Strong cross-functional collaboration and production ownership
More about this role
Shield AI is a venture-backed defense-tech company with the mission of protecting service members and civilians with intelligent systems. Its products include Hivemind autonomy software, V-BAT and X-BAT aircraft, and Aechelon simulation and synthetic reality technologies. With offices and facilities across the U.S., Europe, the Middle East, and Asia-Pacific, Shield AI’s technology actively supports operations worldwide. For more information, visit www.shield.ai . Follow Shield AI on LinkedIn , X , Instagram , and YouTube .
Shield AI is seeking a Data Engineer to build the reliable, governed data foundation for Finance's next generation of planning and decision support. Working on our Databricks platform, you will own reusable integrations, semantic-layer infrastructure, and production data services that support analytics and AI-enabled applications. You will combine engineering rigor with AI-assisted development to increase delivery speed, reliability, and cost efficiency.
- Build and operate scalable pipelines and integrations connecting enterprise data to Finance products.
- Develop semantic-layer infrastructure and governed data access for analytics, planning, and AI...
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