Senior Fabric OneLake Data Modeler
Shape scalable enterprise information models supporting Power BI, self-service analytics, and AI-driven solutions.
Job Summary
The Senior Fabric OneLake Data Modeler is responsible for designing and governing enterprise data models within Microsoft Fabric OneLake. The role ensures data consistency, quality, reusability, and governance across reporting, analytics, AI solutions, and enterprise applications, aligning with Medallion Architecture and Corporate Information Factory (CIF) principles.
Key responsibilities
- Design and maintain conceptual, logical, and physical enterprise data models
- Define facts, dimensions, hierarchies, metrics, relationships, and business entities
- Establish enterprise modeling standards, naming conventions, and metadata management practices
- Develop reusable canonical models and conformed dimensions across business domains
- Review and approve data designs before development
- Govern Bronze, Silver, and Gold layer models, ensuring the Silver layer remains the authoritative source of truth
- Ensure consistent KPI definitions, business logic, data lineage, and referential integrity
- Support Power BI semantic models, self-service analytics, AI solutions, and Fabric Data Agents
- Document models, data dictionaries, business glossaries, KPIs, source-to-target mappings, and lineage
- Collaborate with business stakeholders, architects, engineers, and governance teams
- Conduct model reviews, resolve conflicting business definitions, and mentor junior engineers
- 8+ years of enterprise data modeling experience
- 5+ years of experience designing analytical data warehouses
- Experience with Microsoft Fabric, OneLake, and Medallion Architecture
- Knowledge of Corporate Information Factory methodologies
- Strong SQL and dimensional modeling expertise
- Experience with enterprise semantic models and master data management
- Understanding of star schemas, snowflake schemas, Data Vault, and slowly changing dimensions
- Strong knowledge of primary/foreign keys, cardinality, and referential integrity
- Experience with Power BI and enterprise analytics
- Proficiency in Lucidchart, ERwin, ER/Studio, or equivalent modeling tools
- Experience with Snowflake and Salesforce
- Familiarity with retailer and distributor data ecosystems
- Experience with digital media, consumer engagement, AI, and data agent initiatives
- Trusted enterprise source of truth within the Silver layer
- Consistent KPIs and reusable dimensions across business domains
- Improved data governance, documentation, and lineage
- Reduced development rework and increased self-service analytics adoption
- Faster delivery of governed data products for analytics and AI
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