2 months ago
Base Salary
$160k - $240k/yr
Responsibilities
- Lead discovery and end-to-end enablement for Supply Chain, Manufacturing, and other priority enterprise domains.
- Partner with business and technical leaders to understand processes, source systems, reporting needs, metrics, and data pain points.
- Translate ambiguous business needs into problem statements, prioritized use cases, roadmaps, technical designs, and delivery plans.
- Design and build governed Bronze, Silver, and Gold data assets, domain marts, curated datasets, semantic models, and transformation logic.
- Define canonical domain concepts, facts, dimensions, grain, conformed entities, historical treatment, business rules, and reconciliation approaches.
- Develop and optimize production transformation pipelines using Databricks, SQL, Python, PySpark, and Delta Lake.
- Integrate data across ERP, PLM, MES, MRP, procurement, manufacturing, quality, inventory, supplier, finance, and operational systems.
- Apply and evolve standards for ingestion, modeling, naming, semantics, quality, documentation, lineage, and promotion.
- Partner with Data Engineering, Platform Engineering, and Data Governance teams on reliability, security, access, 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 ability to independently deliver 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, Bronze/Silver/Gold lakehouse patterns, Delta Lake, SQL, and Python and/or PySpark.
- Experience integrating 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 with business and technical stakeholders.
- Preferred experience in aerospace, defense, aviation, autonomous systems, robotics, advanced manufacturing, industrial operations, or regulated environments.
- Preferred experience with Supply Chain and Manufacturing capabilities including demand planning, supply planning, procurement, supplier performance, inventory, production, quality, maintenance, repair, or fulfillment.
- Preferred experience with SAP, Oracle, IFS, Deltek, Costpoint, PLM, MES, MRP, SCM, or comparable enterprise platforms.
- Preferred experience integrating operational measures with Program Finance, cost, inventory valuation, forecasting, planning, or program-performance reporting.
- Preferred experience in controlled, export-sensitive, government, defense, or security-sensitive environments.
Benefits
- Full-time regular employees receive pay within the listed range, bonus, benefits, and equity.
- Temporary employees receive pay within the listed range and a temporary benefits package applicable after 60 days of employment.
- Offers are contingent on a cleared background and possible reference check.
- Military fellows and part-time employees are not eligible for benefits.
About Shield AI
Shield AI builds autonomous systems for military and national security customers, combining its Hivemind autonomy software with V-BAT and X-BAT unmanned aircraft and Aechelon simulation technologies. The privately held company sells hardware, software, and related services to U.S. and allied defense agencies. Founded in 2015 and headquartered in San Diego, it operates across the U.S., Europe, the Middle East, and Asia-Pacific, and its technology is used in operational deployments.