Senior Data Modeler - 6 Month Contract

Description ROLE: Senior Data Modeler – 6 Months Contract      REPORTS TO: Manager, Digital Analytics        LOCATION: Hybrid / Corporate Office in Richmond Hill, Ontario SALARY: $60/h - $80/h About the Role:   We are seeking a senior data modelling specialist to design and evolve the enterprise analytical data model that supports reporting, self-service analytics, planning, and data science. You will translate complex operational data into durable, business-centered structures that make measures, dimensions, and relationships clear and reusable across analytical use cases. This role sits within Data Engineering and works closely with business stakeholders, analysts, BI developers, data engineers, and data governance partners. The primary focus is dimensional modelling and analytical data architecture, not pipeline orchestration or cloud infrastructure engineering. Key Responsibilities:    Design conceptual, logical, and physical analytical data models across major business subject areas. Define the grain of fact tables; design measures, dimensions, hierarchies, keys, and relationships; and select appropriate patterns for historical change. Build conformed dimensions and reusable business entities that support consistent analysis across source systems and functional domains. Abstract transactional and operational source structures into intuitive analytical models rather than reproducing source-system schemas. Develop dimensional models using Kimball-style techniques, including star schemas, role-playing dimensions, bridge tables, factless fact tables, and slowly changing dimensions. Partner with business stakeholders and analysts to understand analytical questions, reporting workflows, definitions, and required levels of detail. Define business meaning, calculation intent, lineage, naming standards, and model documentation so that analytical assets are understandable and governed. Implement models using DBT and validate that delivered structures preserve the intended grain and business logic. Review existing warehouse structures, identify duplication or tightly coupled designs, and guide their evolution towards reusable and supportable analytical models. Provide modelling leadership through design reviews, standards, mentoring, and constructive challenge. What Success Looks Like: Analysts can answer new questions by combining well-defined facts and conformed dimensions without repeatedly rebuilding business logic. Different reports and subject areas use consistent definitions for shared business concepts. Models are stable enough to absorb source-system change while remaining clear to analytical consumers. Fact table grain, history, relationships, and calculation rules are explicit, tested, and documented. Data engineering pipelines implement governed model designs instead of exposing operational structures directly to reporting tools. Qualifications:  7+ years of experience in data warehousing,…