Staff Data and Analytics Engineer Domain Enablement
Shield AI is a U.S. defense-technology company developing mission-autonomy software and autonomous aircraft for military and allied operations.
Funding history
Investors
About Shield AI
Founded in 2015, Shield AI builds Hivemind autonomy software and V-BAT and X-BAT aircraft for operations in contested, GPS- and communications-denied environments. Its current site also presents Aechelon synthetic-reality simulation and Vision Systems detection and tracking products.
Skills
Candidate Availability
Required and preferred rules are kept separate and reflect the wording in the original posting.
About the Role
You will discover business needs and turn them into prioritized data use cases, roadmaps, technical designs, and delivery plans. You will build governed data products, models, pipelines, semantic assets, tests, and documentation for Supply Chain and Manufacturing. You will integrate enterprise data sources and apply quality, security, lineage, and access controls.
Requirements
- 8+ years of data engineering, analytics engineering, BI engineering, data architecture, or blended data-role experience
- Experience delivering end-to-end data and analytics solutions
- Experience in a complex operational domain
- Dimensional modeling and semantic design skills
- Production experience with Databricks, Delta Lake, SQL, Python, and/or PySpark
- Experience integrating complex enterprise systems
- Ability to translate ambiguous business needs into delivery scopes and technical designs
- Communication and stakeholder-partnership skills
Responsibilities
- Lead discovery and enablement for Supply Chain and Manufacturing domains
- Translate business needs into use cases, roadmaps, technical designs, and delivery plans
- Design and build governed data products and analytical assets
- Define canonical domain concepts, facts, dimensions, business rules, and reconciliation approaches
- Build and optimize transformation pipelines using Databricks, SQL, Python, PySpark, and Delta Lake
- Integrate data from enterprise operational systems
- Apply data quality, documentation, lineage, security, and access standards
- Partner with business leaders, Data Engineering, Platform Engineering, and Data Governance
Benefits
- Bonus
- Equity