Senior Data Modeller (Microsoft Fabric Star Schema)

MANDATORY - Must have experience in Dimensional Modelling Star Schema and Microsoft Fabric NO FRESHER WILL BE PREFERRED We are looking for Senior Data Modeller (Microsoft Fabric Star Schema) as a Full Time for our IT Company. Location- Remote Experience- 7+ years Budget- As per company standards Notice Period- Immediate Joiner Mandatory Experience Enterprise data modelling and data warehousing. Conceptual, logical and physical data modelling. Dimensional modelling, including facts, dimensions, star schema and conformed dimensions. Designing analytics-ready datasets for BI and reporting. Strong SQL. Experience with cloud data platforms or modern data lake/lakehouse architectures. Understanding of Bronze, Silver and Gold data layers. Working with architects, data engineers, analysts and business stakeholders. Documenting data definitions, mappings, lineage and model assumptions. Preferred Experience Microsoft Fabric. Fabric Lakehouse and Fabric Warehouse. OneLake. Power BI semantic models. Delta Lake. Microsoft Purview. Azure data services. Data product-oriented delivery. Data quality and metadata management. Agile delivery environments. Role Summary We are looking for a Data Modeller to support a Microsoft Fabric data platform programme for a large enterprise client. The client is building a more product-oriented data organisation, where trusted data assets are created once, governed properly and reused across business domains. This role will help shape the data models that sit at the heart of that approach. The successful candidate will work across source system onboarding, Fabric Lakehouse and Warehouse design, reusable Silver-layer datasets, Gold-layer analytical models and Power BI semantic consumption. The role is not limited to drawing data models. It requires someone who can understand business processes, challenge unclear definitions, define model grain, agree common entities and help engineering teams turn source data into trusted, usable data assets. This would suit someone with strong dimensional modelling experience who has worked on modern cloud data platforms and is comfortable operating between business stakeholders, architects, engineers, governance teams and BI/reporting users. Key Responsibilities Design conceptual, logical and physical data models for enterprise data onboarding and analytics use cases. Define modelling patterns for Fabric Lakehouse, Fabric Warehouse and Power BI semantic consumption. Support the implementation of Bronze, Silver and Gold data layers using Medallion Architecture principles. Design conformed dimensions, fact tables, reference data structures, master data views and analytics-ready datasets. Define model grain, business keys, surrogate keys, relationships, hierarchies and history handling. Create source-to-target mappings and work with engineers to turn modelling designs into working data assets. Help define reusable Silver-layer datasets that are more than cleansed copies of source systems. Design Gold-layer models around reporting, KPIs, business questions and decision-making needs. Work with domain teams to understand business processes, data ownership, key metrics and analytical requirements. Support Power BI semantic model design by ensuring data structures are clear, performant and business-friendly. Document business definitions, model assumptions, lineage, data quality rules and known limitations. Work with governance teams to align models with naming standards, glossary terms, metadata and access requirements. Participate in architecture reviews, data model reviews and discussions around shared enterprise definitions. Help reduce duplicated reporting datasets and inconsistent KPI logic across the organisation. Expected Outputs Conceptual and logical data models. Physical model designs for Fabric Lakehouse and Warehouse. Entity relationship diagrams. Dimensional models with facts, dimensions and defined grain. Source-to-target mapping documents. Data product or dataset specifications. Data dictionaries and business definitions. Lineage and dependency documentation. Data quality rule definitions. Naming standards and modelling design patterns. Inputs into Power BI semantic model design. Model review packs for architecture or governance forums. Required Skills Strong hands-on experience in enterprise data modelling and data warehousing. Confident with dimensional modelling including star schemas, facts, dimensions, conformed dimensions and slowly changing dimensions. Strong SQL — able to read transformation logic, understand joins and aggregations. Understanding of modern cloud data platforms and Lakehouse concepts. Experience with Microsoft Fabric strongly preferred — especially Fabric Lakehouse, Fabric Warehouse, OneLake and Power BI semantic models. Understanding of governance in data modelling — naming standards, definitions, ownership, lineage, quality expectations, access controls and metadata.