Databricks Data Modeler Consultant

We are seeking a Databricks Data Modeler (Enterprise Supply Chain & Analytics) to design, optimize, and maintain enterprise data modeling solutions on Microsoft Azure. This role spans supply chain and cross-enterprise analytics, delivering trusted datasets consumed by reporting/dashboards, AI/ML pipelines, and application integrations. You will work within Unity Catalog to ensure governed, well-documented, and secure data products across the organization.

Location:

US Remote

Type:
Contract

• Design and develop enterprise-scale data models in Databricks across Bronze/Silver/Gold layers supporting supply chain analytics, demand/supply planning, inventory, procurement, and order management.
• Build and maintain semantic models and KPIs covering forecast accuracy, inventory visibility (WIP/FG/in-transit), aging, service-level metrics, supplier lead time/OTIF, backorders, shipment/receipt traceability, and product/item master hierarchies.
• Implement Delta Lake modeling patterns: incremental processing, upserts/merges, late-arriving data handling, SCD, surrogate key strategies, partitioning, and ZORDER optimization.
• Deliver consumption-ready datasets for reporting (consistent grains and metric definitions), AI/ML (feature tables, training/serving datasets), and application integrations.
• Collaborate with engineering and business stakeholders to confirm data grain, business rules, and reconciliation requirements.
• Establish and enforce data modeling standards: naming conventions, schema organization, documentation, model ownership, and data contracts for critical datasets.
• Implement automated data quality validations.
• Manage Unity Catalog governance: catalogs/schemas, access controls, metadata, lineage, and discoverability.
• Support CI/CD practices for data assets (Git-based development, testing gates).
• Troubleshoot and improve model performance, correctness, and refresh reliability.

• 4+ years in data modeling/analytics engineering with Databricks (Databricks SQL and/or Spark).
• Strong fundamentals in dimensional modeling (star/snowflake), SCD patterns, grain definition, and master data modeling.
• Strong SQL skills and performance tuning.
• Experience with Azure data platform and Databricks on Azure.
• Proven Unity Catalog experience.
• Familiarity with automated data quality/validation frameworks.

• Supply chain dataset experience with Databricks SQL and Spark.
• Enterprise application integration patterns (curated tables with stable schemas, event-driven or batch consumption).

• Governance: Unity Catalog — permissions, ownership, lineage, and metadata management
• Platform: Azure — Databricks on Azure, storage, and security concepts
• Quality: Automated validation and reconciliation strategies
• Tooling: Git-based workflows, CI/CD