Senior Data Modeler

Tundra Technical Solutions; Richmond Hill; Hybrid; CAD 96,000 - 110,000; Full time

Benefits offered by this job

Medical, dental, vision benefits

Retirement benefits

Job summary

Tundra Technical Solutions in Richmond Hill, Ontario is 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.

Qualifications

• 7+ years of experience in data warehousing, analytics engineering, BI, or data architecture with hands-on analytical data modeling.
• 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, and many-to-many relationships.
• Experience creating conceptual, logical, and physical models across multiple source systems.
• Strong SQL skills to profile data, validate assumptions, and test models against business processes.
• Working knowledge of dbt or similar SQL-based transformation frameworks.
• Experience modeling data for reporting, BI, semantic models, and self-service analytics.
• Ability to facilitate requirements and model-design discussions with business and technical participants.
• Ability to explain modelling choices, trade-offs, and constraints with diagrams and documentation.
• Experience reviewing models for quality, usability, and alignment with standards.
• Exposure to Git and automated deployment practices for database changes.

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 patterns for historical change.
• Build conformed dimensions and reusable business entities to support consistent analysis across source systems.
• Abstract transactional structures into intuitive analytical models rather than reproducing source schemas.
• Collaborate with stakeholders to understand analytical questions and reporting needs.
• Define business meaning, calculation intent, lineage, naming standards, and model documentation.
• Implement models using DBT and validate grain and logic.
• Review warehouse structures and guide evolution toward reusable models.
• Provide modelling leadership through reviews, standards, mentoring, and challenge.

Skills

Dimensional modelling

SQL skills

Data warehousing

Stakeholder collaboration

Analytical data architecture

Data governance

Education

BSc/MSc in Computer Science / Information Systems / Engineering / Math / Analytics

Tools

dbt

Git

Snowflake

Power BI

Job description

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.
• 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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