{"id":1260830,"url":"https://alion.io/job/shield-ai-staff-data-analytics-engineer-domain-enablement-r6112","title":"Staff Data & Analytics Engineer, Domain Enablement (R6112)","company":{"id":50,"name":"Shield AI","domain":"shield.ai","url":"https://alion.io/company/shield-ai","size_band":"1001-5000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Lever","truth_index":{"grade":"B","score":74,"open_postings":76,"ghost_share":0,"stale_share":0.842,"repost_share":0,"time_to_fill_p50_days":69,"computed_at":"2026-10-24T06:02:35Z"}},"role":"Data Science","role_family":"Data Science","seniority":"staff","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Dallas, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":{"min":160000,"max":240000,"currency":"USD","period":"year","gross":null,"usd_annual":240000},"salary_estimate":null,"experience_years_min":8,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Databricks","optional":false},{"name":"Delta Lake","optional":false},{"name":"Dimensional Modeling","optional":false},{"name":"Platform Engineering","optional":false},{"name":"pySpark","optional":false},{"name":"Python","optional":false},{"name":"SQL","optional":false},{"name":"Spark","optional":true}],"status":"live","first_seen_at":"2026-09-25T19:26:13Z","employer_posted_date":"2026-09-25","last_verified_at":"2026-10-24T13:28:26Z","board_verified":true,"closed_at":null,"days_open":28,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":28},"description":"Job Description:\nThe 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.\nThis 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.\nThe initial focus for this role 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 as enterprise priorities evolve.\nThis is not a dashboard-development role. The Staff Data & Analytics Engineer will establish the domain data foundations and technical direction needed to deliver durable data products and accelerate future use cases. 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.\nWhat you'll do:\nLead discovery and end-to-end enablement for complex Supply Chain and Manufacturing domains initially, with flexibility to support other priority enterprise domains as business needs evolve. \nPartner directly with Supply Chain, Manufacturing, and Operations leaders to understand business processes, decisions, source systems, reporting needs, metrics, and pain points; collaborate with Finance, Program Finance, Engineering, IT, Security, and other partners where processes, systems, or data intersect. \nTranslate ambiguous business needs into clear problem statements, prioritized use cases, phased roadmaps, technical designs, and achievable delivery plans. \nDesign and build governed data products across the data stack, including source-system assessment and integration requirements; Bronze, Silver, and Gold data assets; transformation logic; domain marts; curated datasets; semantic models; testing; documentation; and production-readiness controls. \nDefine canonical domain concepts, grain, facts, dimensions, conformed entities, historical treatment, business rules, and reconciliation approaches for high-value operational and analytical data. \nDesign 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, aligned to established enterprise patterns and standards. \nWork across ERP, PLM, MES, MRP, procurement, manufacturing, quality, inventory, supplier, finance, and operational systems to create integrated and understandable data products. \nDevelop and optimize transformation pipelines using Databricks, SQL, Python, PySpark, Delta Lake, and related technologies as appropriate. \nApply enterprise ingestion, modeling, naming, semantic, quality, documentation, lineage, and promotion standards across Bronze, Silver, and Gold layers; identify where those standards need to evolve to support complex operational domains. \nPartner with Data Engineering, Platform Engineering, and Data Governance to apply shared standards and establish the ingestion, reliability, security, access, lineage, metadata, stewardship, and quality controls needed for domain data products. \nRequired qualifications:\n8+ years of experience in data engineering, analytics engineering, BI engineering, data architecture, or a blended data role. \nDemonstrated experience independently delivering end-to-end data and analytics solutions-from source-system discovery and integration through governed, business-consumable data products. \nStrong experience in at least one complex operational domain, such as Supply Chain, Manufacturing, Procurement, Planning, Logistics, Operations, Industrial, or Program Management. \nStrong dimensional modeling and semantic design skills, including facts, dimensions, grain, conformed dimensions, historical treatment, and auditable business logic. \nHands-on production experience with Databricks, including Bronze, Silver, and Gold lakehouse patterns, Delta Lake, SQL, and Python and/or PySpark. \nExperience operating in controlled, export-sensitive, government, defense, or security-sensitive environments. \nExperience integrating data from complex enterprise systems, such as ERP, PLM, MES, MRP, procurement, inventory, supplier, quality, production, or financial systems. \nAbility to translate ambiguous business needs into practical delivery scopes, technical designs, and prioritized roadmaps. \nStrong communication skills and comfort partnering directly with business and technical stakeholders. \nPreferred qualifications:\nExperience in aerospace, defense, aviation, autonomous systems, robotics, advanced manufacturing, industrial operations, or similarly complex and regulated environments. \nExperience 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. \nExperience with systems such as SAP, Oracle, IFS, Deltek, Costpoint, PLM, MES, MRP, SCM, or comparable enterprise platforms. \nExperience integrating operational measures with Program Finance, cost, inventory valuation, forecasting, planning, or program-performance reporting. \nExperience operating in controlled, export-sensitive, government, defense, or security-sensitive 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