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Shield AI

Posted 4 days ago

Open

Data Engineer, Finance (R6329)

San DiegoOn-site

AI Summary

Builds and operates scalable data pipelines and semantic-layer infrastructure on Databricks to support Finance analytics, planning, and AI-enabled applications.

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.

Job Description:

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.

What you'll do:

  • 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 applications.
  • Establish end-to-end pipeline observability, data-quality controls, and resilient operations.
  • Engineer the services and integrations behind Databricks Genie and other AI-enabled Finance workflows.
  • Use AI coding assistants to accelerate development while validating correctness, security, and performance.
  • Apply FinOps practices to manage platform spend and optimize cost without compromising service quality.
  • Partner with analytics engineers and enterprise teams on architecture, data contracts, and sustainable ownership.

    • Required qualifications:

  • 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.

    • Preferred qualifications:

  • Experience with Databricks, Delta Lake, cloud infrastructure, and deployment automation.
  • Experience developing AI application backends, model integrations, or LLM-based workflows.
  • Experience with FinOps, financial data, or enterprise-system integrations.

    • Skills

    AI Coding AssistantsCloud Data PlatformsDatabricksData ModelingData OrchestrationData-quality ControlsDelta LakeFinOpsLLM IntegrationObservabilityPySparkPythonSnowflake CortexSQL

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