Data Modeler with Databricks

Position Summary

The Databricks Data Modeler is responsible for defining enterprise data structures, conceptual models, logical models, and physical implementations that support analytics, AI, reporting, and operational data products. The role ensures consistency, scalability, governance, and business alignment across the Databricks ecosystem.

Key Responsibilities

• Design conceptual, logical, and physical data models.
• Develop enterprise-wide business and domain data models.
• Define standardized data structures for Databricks Lakehouse implementations.
• Create dimensional models for analytics and reporting.
• Design canonical data models to support cross-domain integration.
• Collaborate with business stakeholders to define data requirements.
• Establish naming standards, metadata standards, and modeling best practices.
• Support Master Data Management (MDM) and data governance efforts.
• Ensure models align with AI, ML, and enterprise reporting needs.
• Maintain data dictionaries, lineage documentation, and metadata repositories.

Required Skills

• Data Modeling
• Databricks Lakehouse Architecture
• SQL
• Dimensional Modeling
• Data Warehouse Design
• ER Modeling
• Data Governance
• Metadata Management

Preferred Skills

• Healthcare Data Models
• Kimball Methodology
• Data Vault 2.0
• Unity Catalog
• Master Data Management
• Enterprise Information Architecture

Experience

• 5+ years in Data Modeling
• Experience designing scalable cloud-based data models
• Experience supporting Databricks implementations

Key Deliverables

• Enterprise Data Models
• Subject Area Models
• Dimensional Models
• Data Dictionaries
• Business Glossaries
• Source-to-Target Mapping Specifications
• Data Standards and Governance Artifacts