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Shield AI is a venture-backed defense-tech company developing autonomous systems, aircraft, and simulation technologies for military and civilian protection. This Staff-level Data & Analytics Engineer role focuses on domain enablement for Supply Chain and Manufacturing, with potential expansion to other enterprise domains.
You will lead end-to-end discovery and enablement for complex operational domains, partnering directly with Supply Chain, Manufacturing, Operations, Finance, Engineering, and IT leaders to understand business processes, systems, reporting needs, and pain points. You'll translate ambiguous business requirements into clear problem statements, prioritized use cases, phased roadmaps, and technical designs.
Key responsibilities include designing and building governed data products across the full data stack—from source-system assessment and integration through Bronze, Silver, and Gold data assets, transformation logic, domain marts, curated datasets, and semantic models. You'll define canonical domain concepts (facts, dimensions, grains, conformed entities, historical treatment, business rules) and deliver data models for Supply Chain and Manufacturing concepts such as parts, materials, suppliers, purchase orders, demand, supply, inventory, work orders, production, quality, cost, and fulfillment.
You'll work across ERP, PLM, MES, MRP, procurement, manufacturing, quality, inventory, supplier, finance, and operational systems to create integrated, understandable data products. You'll develop and optimize transformation pipelines using Databricks, SQL, Python, PySpark, and Delta Lake, applying enterprise standards for ingestion, modeling, naming, semantics, quality, documentation, lineage, and promotion. You'll partner with Data Engineering, Platform Engineering, and Data Governance to establish shared standards and controls for domain data products.
REQUIREMENTS:
- 8+ years of experience in data engineering, analytics engineering, BI engineering, data architecture, or blended data roles
- Demonstrated experience independently delivering end-to-end data and analytics solutions from source-system discovery through governed, business-consumable data products
- Strong experience in at least one complex operational domain (Supply Chain, Manufacturing, Procurement, Planning, Logistics, Operations, Industrial, or Program Management)
- Strong dimensional modeling and semantic design skills (facts, dimensions, grain, conformed dimensions, historical treatment, auditable business logic)
- Hands-on production experience with Databricks, including Bronze/Silver/Gold lakehouse patterns, Delta Lake, SQL, Python, and/or PySpark
- Experience integrating data from complex enterprise systems (ERP, PLM, MES, MRP, procurement, inventory, supplier, quality, production, financial systems)
- Ability to translate ambiguous business needs into practical delivery scopes, technical designs, and prioritized roadmaps
- Strong communication skills and comfort partnering with business and technical stakeholders
PREFERRED:
- Experience in aerospace, defense, aviation, autonomous systems, robotics, advanced manufacturing, industrial operations, or similarly complex regulated environments
- Experience supporting Supply Chain or Manufacturing capabilities (demand planning, supply planning, procurement, supplier performance, inventory/materials management, production, quality, maintenance, repair, fulfillment)
- Experience with SAP, Oracle, IFS, Deltek, Costpoint, PLM, MES, MRP, SCM, or comparable enterprise platforms
- Experience integrating operational measures with Program Finance, cost, inventory valuation, forecasting, planning, or program-performance reporting
- Experience in controlled, export-sensitive, government, defense, or security-sensitive environments
