Staff Data & Analytics Engineer, Domain Enablement

DataJobs; Dallas (TX); On-site; USD 160,000 - 240,000; Full time

Benefits offered by this job

Equity

Bonus

Benefits

Job summary

SHIELD AI is seeking a Staff Data & Analytics Engineer for Domain Enablement in Dallas, TX. You will lead discovery and end-to-end enablement for Supply Chain and Manufacturing, building governed data products across the data stack with Bronze/Silver/Gold layers and semantic models.

You will collaborate with leaders across Finance, Engineering, IT, Security, and Operations to translate needs into prioritized roadmaps, patterns, and delivery plans.

Qualifications

• 8+ years of data engineering, analytics engineering, BI engineering, data architecture, or blended data role.
• Proven ability to deliver end-to-end data and analytics solutions from source-system discovery to governed data products.
• Strong experience in Supply Chain, Manufacturing, Procurement, Planning, Logistics, Operations, Industrial, or Program Management.

Responsibilities

• Lead end-to-end domain enablement for Supply Chain and Manufacturing domains.
• Collaborate with Supply Chain, Manufacturing, and Operations leaders to map processes, data needs, metrics, and pain points.
• Work with Finance, Engineering, IT, Security, and other teams when data intersects across systems.
• Translate ambiguous business needs into practical delivery scopes, roadmaps, and designs.
• Design and build governed data products: source-system assessment, Bronze/Silver/Gold assets, lineage, testing, and documentation.
• Define canonical domain concepts: grain, facts, dimensions, conformed entities, historical treatment, and business rules.
• Deliver governed data models and analytical assets for parts, materials, suppliers, orders, demand, inventory, work orders, production, quality, cost, and fulfillment.
• Integrate data across ERP, PLM, MES, MRP, procurement, inventory, supplier, quality, production and finance systems.
• Develop and optimize transformations using Databricks, SQL, Python, PySpark, and Delta Lake.

Skills

Domain discovery

Senior leadership

Communication with execs

Problem translation

Tools

Databricks

Delta Lake

SQL

Python

PySpark

ERP

PLM

MES

MRP

Job description

SHIELD AI is building an enterprise data platform to support mission‑critical business domains, and this role focuses on turning complex operations into governed, business‑ready data products. As a Staff Data & Analytics Engineer for Domain Enablement, you will lead domain discovery and end‑to‑end enablement with an initial focus on Supply Chain and Manufacturing, while staying flexible to support other enterprise priorities as needs evolve.

This is a senior, hands‑on position based in Dallas, TX (onsite), with a target salary range of USD 160,000 - 240,000 per year and a requirement of 8+ years of relevant experience.

What you’ll do

• Lead discovery and end‑to‑end domain enablement for complex Supply Chain and Manufacturing domains initially, with flexibility to support other priority enterprise domains.
• Work directly with Supply Chain, Manufacturing, and Operations leaders to understand business processes, decisions, source systems, reporting needs, metrics, and pain points.
• Collaborate with partners across Finance, Program Finance, Engineering, IT, Security, and other teams when processes, systems, or data intersect.
• Translate ambiguous business needs into clear problem statements, prioritized use cases, phased roadmaps, technical designs, and delivery plans.
• Design and build governed data products across the data stack, including source‑system assessment and integration requirements; Bronze, Silver, and Gold assets; transformation logic; domain marts; curated datasets; semantic models; testing; documentation; and production‑readiness controls.
• Define canonical domain concepts such as grain, facts, dimensions, conformed entities, historical treatment, business rules, and reconciliation approaches for high‑value operational and analytical data.
• Deliver governed Supply Chain and Manufacturing data models and analytical assets for concepts including parts, materials, suppliers, purchase orders, demand, supply, inventory, work orders, production, quality, cost, and fulfillment, aligned to established enterprise patterns and standards.
• Integrate across enterprise systems spanning ERP, PLM, MES, MRP, procurement, manufacturing, quality, inventory, supplier, finance, and operational systems.
• Develop and optimize transformation pipelines using Databricks, SQL, Python, PySpark, Delta Lake, and related technologies as appropriate.
• Apply ingestion, modeling, naming, semantic, quality, documentation, lineage, and promotion standards across Bronze/Silver/Gold layers, and identify where those standards must evolve for complex operational domains.
• Partner with Data Engineering, Platform Engineering, and Data Governance to apply shared standards and set ingestion, reliability, security, access, lineage, metadata, stewardship, and quality controls for domain data products.

Required qualifications

• 8+ years of experience in data engineering, analytics engineering, BI engineering, data architecture, or a blended data role.
• Proven 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, including Bronze, Silver, and Gold lakehouse patterns, Delta Lake, SQL, and Python and/or PySpark.
• Experience integrating data from 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.

Technologies

• Databricks
• SQL
• Python
• PySpark
• Delta Lake
• ERP, PLM, MES, MRP

Compensation & benefits

• Pay range: $160,000 - $240,000 a year
• Full‑time regular employee offer package: Pay within the range listed + Bonus + Benefits + Equity
• Temporary employee offer package: Pay within the range listed above + temporary benefits package (applicable after 60 days of employment)

Offer conditions

• All offers are contingent on a cleared background and possible reference check.
• Military fellows and part‑time employees are not eligible for benefits.