Staff Data & Analytics Engineer – Domain Enablement

About the role

Shield AI is seeking a senior Staff Data & Analytics Engineer to enable complex business domains on its enterprise data platform. The role will focus initially on Supply Chain and Manufacturing, building governed data products that make operational data trustworthy and scalable for decision‑making.

Key responsibilities

• Lead discovery and end‑to‑end enablement of Supply Chain and Manufacturing data domains, translating business needs into clear problem statements and phased roadmaps.
• Design and build governed data products across Bronze, Silver, and Gold lakehouse layers, including source‑system assessment, transformation logic, domain marts, and semantic models.
• Define canonical domain concepts, grain, facts, dimensions, conformed entities, and business rules for high‑value operational data.
• Develop and optimise transformation pipelines using Databricks, SQL, Python, PySpark and Delta Lake.
• Partner with Data Engineering, Platform Engineering and Data Governance to apply shared standards and ensure data quality, security and lineage.

Required profile

• 8+ years of experience in data engineering, analytics engineering, BI engineering or data architecture.
• Proven ability to deliver end‑to‑end data solutions from source‑system discovery to governed, business‑consumable data products.
• Strong experience in a complex operational domain such as Supply Chain, Manufacturing, Procurement or Logistics.
• Hands‑on production experience with Databricks lakehouse patterns (Bronze/Silver/Gold) and Delta Lake.
• Excellent communication skills and comfort partnering directly with business and technical stakeholders.

Required skills

• Databricks
• SQL
• Python
• PySpark
• Delta Lake
• Dimensional modeling
• Semantic design
• Data modeling
• ERP integration (e.g., SAP, Oracle, IFS, Costpoint)
• PLM, MES, MRP systems