Staff Data & Analytics Engineer, Domain Enablement (R6112)

The Staff Data & Analytics Engineer, Domain Enablement is a senior, hands-on role responsible for enabling complex business domains on Shield AI's enterprise data platform. This person will lead discovery, scope high-value data and analytics opportunities, and deliver governed data products that make operational data more usable, trustworthy, and scalable for business decision-making. The role works across the data stack, from understanding source systems and defining integration needs through transformation, modeling, semantic design, quality controls, documentation, and business consumption. The initial focus is Supply Chain and Manufacturing, including the systems, processes, and data required to support planning, procurement, suppliers, materials, inventory, production, quality, fulfillment, cost, and program operations. Over time, the role may expand to support other complex domains. This is not a dashboard-development role. The ideal candidate combines strong technical depth with the ability to work directly with business partners, clarify ambiguity, and turn complex operational needs into practical, staged solutions.

Responsibilities

Lead discovery and end-to-end enablement for complex Supply Chain and Manufacturing domains, with flexibility to support other priority enterprise domains; Partner directly with Supply Chain, Manufacturing, and Operations leaders to understand business processes, decisions, source systems, reporting needs, metrics, and pain points; Translate ambiguous business needs into clear problem statements, prioritized use cases, phased roadmaps, technical designs, and achievable delivery plans; Design and build governed data products across the data stack, including source-system assessment, integration requirements, Bronze, Silver, and Gold data assets, transformation logic, domain marts, curated datasets, semantic models, testing, documentation, and production-readiness controls; Define canonical domain concepts, grain, facts, dimensions, conformed entities, historical treatment, business rules, and reconciliation approaches; Design and deliver governed Supply Chain and Manufacturing data models and analytical assets for concepts such as parts, materials, suppliers, purchase orders, demand, supply, inventory, work orders, production, quality, cost, and fulfillment; Work across ERP, PLM, MES, MRP, procurement, manufacturing, quality, inventory, supplier, finance, and operational systems to create integrated data products; Develop and optimize transformation pipelines using Databricks, SQL, Python, PySpark, Delta Lake, and related technologies; Apply enterprise ingestion, modeling, naming, semantic, quality, documentation, lineage, and promotion standards across Bronze, Silver, and Gold layers; Partner with Data Engineering, Platform Engineering, and Data Governance to establish ingestion, reliability, security, access, lineage, metadata, stewardship, and quality controls

Requirements

8+ years of experience in data engineering, analytics engineering, BI engineering, data architecture, or a blended data role; Demonstrated experience independently delivering end-to-end data and analytics solutions, from source-system discovery and integration through governed, business-consumable data products; Strong experience in at least one complex operational domain, such as Supply Chain, Manufacturing, Procurement, Planning, Logistics, Operations, Industrial, or Program Management; Strong dimensional modeling and semantic design skills, including facts, dimensions, grain, conformed dimensions, historical treatment, and auditable business logic; Hands-on production experience with Databricks, including Bronze, Silver, and Gold lakehouse patterns, Delta Lake, SQL, and Python and/or PySpark; Experience operating in controlled, export-sensitive, government, defense, or security-sensitive environments; Experience integrating data from complex enterprise systems, such as ERP, PLM, MES, MRP, procurement, inventory, supplier, quality, production, or financial systems; Ability to translate ambiguous business needs into practical delivery scopes, technical designs, and prioritized roadmaps; Strong communication skills and comfort partnering directly with business and technical stakeholders

Nice to have

Experience in aerospace, defense, aviation, autonomous systems, robotics, advanced manufacturing, industrial operations, or similarly complex and regulated environments; Experience supporting Supply Chain or Manufacturing capabilities such as demand planning, supply planning, procurement, supplier performance, inventory and materials management, production, quality, maintenance, repair, or fulfillment; Experience with systems such as 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 operating in controlled, export-sensitive, government, defense, or security-sensitive environments

Benefits

Bonus (full-time regular employees); Benefits (full-time regular employees); Equity (full-time regular employees); Temporary benefits package applicable after 60 days of employment (temporary employees)