Staff Data & Analytics Engineer: Supply Chain Domain

Lever, Inc.; Dallas, Northern (TX, KY); Hybrid; USD 160,000 - 240,000; Full time

Job summary

Shield AI is seeking a Staff Data & Analytics Engineer, Domain Enablement, to lead end-to-end enablement for Supply Chain and Manufacturing domains on the enterprise data platform. You will partner with business leaders to map processes, define data needs, and deliver durable data products that are governable and scalable.

The role requires strong technical depth with Databricks, Delta Lake, SQL, and Python/PySpark, and the ability to work with cross-functional partners to implement staged

Qualifications

• 8+ years in data engineering, analytics engineering, BI engineering, or data architecture.
• Proven end-to-end data and analytics delivery from source to governed data products.
• Strong experience in at least one domain (e.g., Supply Chain, Manufacturing, Procurement).
• Hands-on with Databricks, Delta Lake, SQL and Python/PySpark.

Responsibilities

• Lead discovery and end-to-end enablement for complex Supply Chain and Manufacturing domains.
• Collaborate with leaders to understand processes, source systems, metrics and pain points across functions.
• Translate ambiguous needs into problem statements, roadmaps, and technical designs.
• Design and build governed data products across Bronze to Gold layers with data models and lineage.
• Define canonical domain concepts, grain, facts, dimensions, and reconciliation rules.
• Work with ERP, PLM, MES, MRP, procurement, inventory, and other systems to deliver integrated data products.

Skills

Data engineering

Analytics engineering

BI engineering

Data architecture

Tools

Databricks

Delta Lake

SQL

Python

PySpark

Job description

Shield AI is seeking a Staff Data & Analytics Engineer, Domain Enablement, to lead end-to-end enablement for Supply Chain and Manufacturing domains on the enterprise data platform. You will partner with business leaders to map processes, define data needs, and deliver durable data products that are governable and scalable.

The role requires strong technical depth with Databricks, Delta Lake, SQL, and Python/PySpark, and the ability to work with cross-functional partners to implement staged