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 https://shield.ai/. Follow Shield AI on LinkedIn https://www.linkedin.com/company/shield-ai, X https://x.com/shieldaitech, Instagram https://www.instagram.com/shield_ai, and YouTube https://www.youtube.com/@Shield_AI.
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:
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- 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:
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- Bachelor’s degree in computer science or a related technical or quantitative field and a minimum of 2 years of related experience.
- 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:
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- 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.
#LI-RS3
#LB
Full-time regular employee offer package:
Pay within range listed + Bonus + Benefits + Equity
Temporary employee offer package:
Pay within range listed above + temporary benefits package (applicable after 60 days of employment)
Salary compensation is influenced by a wide array of factors including but not limited to skill set, level of experience, licenses and certifications, and specific work location. All offers are contingent on a cleared background and possible reference check. Military fellows and part-time employees are not eligible for benefits. Please speak to your talent acquisition representative for more information.
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