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Senior Staff Data Engineer, Databricks (R6508)

Shield AI · United States

$145k - $220k
On-site
Full-time
Senior
Enterprise Operations Division

Posted November 3, 2026

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AI Summary

Shield AI is seeking a Senior Staff Data Engineer to design and build batch and streaming ingestion pipelines from enterprise source systems into a Databricks lakehouse using Delta Lake. The role owns Bronze-layer ingestion (raw landing, metadata, traceability) and Silver-layer cleansing and quality enforcement, while defining reusable engineering patterns for other domains. It also covers Databricks platform setup (catalogs, schemas, service principals, orchestration) and CI/CD for data platform assets. The role is interesting for its platform-level scope and its impact across a defense-tech company's data operations.

Job Description

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. 

Role Summary

The Senior Staff Data Engineer will help build and operate the enterprise lakehouse on Databricks, creating the governed data foundation that supports multiple business domains and downstream analytics. This is a hands-on role, responsible for scalable ingestion, reliable data processing, and strong technical controls across the Bronze and Silver layers of the medallion architecture.
 
This role is not limited to moving data from point A to point B. The Data Engineer is expected to understand the meaning, sensitivity, classification, and intended use of the data flowing through the pipelines they build, and to apply that understanding when designing controls, access patterns, data quality checks, and segregation boundaries appropriate for a highly regulated environment.

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