Senior Data Modeler

ROLE: Senior Data Modeler – 6 Months Contract

REPORTS TO: Manager, Digital Analytics

LOCATION: Hybrid / Corporate Office in Richmond Hill, Ontario

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, analytics engineering, business intelligence, data architecture, or a related discipline, with substantial hands-on responsibility for analytical data modelling.
• Demonstrated experience designing dimensional data warehouses using Kimball methodologies.
• Deep understanding of dimensional modelling concepts, including fact table grain, conformed dimensions, slowly changing dimensions, surrogate keys, hierarchies, additive and non-additive measures, and many-to-many relationships.
• Experience creating conceptual, logical, and physical models that abstract data from multiple transactional source systems.
• Strong SQL skills and the ability to profile source data, validate assumptions, and test whether a model represents business processes correctly.
• Working knowledge of dbt or similar SQL-based transformation frameworks.
• Experience modelling data for reporting, BI, semantic models, and self-service analytics.
• Ability to facilitate requirements and model-design discussions with both business and technical participants.
• Ability to explain modelling choices, trade-offs, and constraints clearly through diagrams, definitions, examples, and design documentation.
• Experience reviewing implemented models for structural quality, usability, consistency, and alignment with modelling standards.
• Experience modelling data across multiple enterprise applications or integrating similar business concepts from different source systems.
• Familiarity with medallion-style data platform architecture and the role of curated, business-oriented models within that architecture.
• Exposure to Git and automated deployment practices for database and transformation changes.

Preferred Qualifications:

• Experience implementing analytical models in Snowflake or a comparable cloud data platform.
• Experience supporting Power BI or another enterprise BI platform, including collaboration on semantic layer design.
• Experience with data governance, metadata management, lineage, data quality rules, and business glossaries.

Education:

• Bachelor's or master's degree in computer science, information systems, engineering, mathematics, business analytics, or a related field, or equivalent practical experience.

The pay range that the employer reasonably expects to pay for this position is between CA$70.00 and CA$80.00

Our voluntary benefits offering includes medical, dental, vision and retirement benefits.

This posting is for an existing vacancy.

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Tundra Technical Solutions is a global workforce and technology delivery firm, ranked by Staffing Industry Analysts as one of the largest in North America. At Tundra, we aren't just hiring top talent at the world's most recognizable brands; we are pioneers of social recruitment. We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other legally protected characteristics. We welcome and encourage diversity in the workplace.

We use artificial intelligence tools to help our recruiters screen and assess talent. These tools do not replace human decision making in the process.

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