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The Data Modeller will be involved in the design of enterprise and domain-level data models across Microsoft Fabric. This includes conceptual, logical and physical modelling for new data sources, business domains and reporting use cases.
A key part of the role will be to help define reusable datasets across the Bronze, Silver and Gold layers. Bronze will largely reflect raw or source-aligned data. Silver should become the trusted, standardised and reusable business-aligned layer. Gold should support consumption through reporting, semantic models, dashboards, analytics and future AI use cases.
The role will work closely with Data Engineers to define source-to-target mappings, transformation rules, keys, relationships, data quality checks and history handling. It will also involve working with Analytics Engineers and Power BI teams to make sure downstream semantic models are built on consistent and well-understood data structures.
The candidate will also support the definition of common enterprise entities, such as customer, product, supplier, location, transaction, order, contract, employee or other client-specific business concepts. The exact domains will depend on the systems being onboarded, but the principle is the same: create models that are clear, reusable and aligned to business meaning.
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The role is expected to produce practical modelling artefacts that can be used by engineers, analysts, architects and business teams. Typical outputs include:
● 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.
● 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.
● 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.
Provides AI, data analytics, and digital transformation consulting services.
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Senior · 5+ years experience
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