Data Solutions Architect: Semantic Modeling & Governance

Triton Environmental Consultants, Ltd.

Calgary

On-site

CAD 110,000 - 140,000

Full time

14 days+
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Job summary

SMART Technologies is seeking a Data Solutions Specialist to connect business needs with data engineering and reporting. You will design semantic models, govern KPI definitions, and ensure trustworthy data foundations for reports, self-serve analytics, and AI.

You will collaborate with Sales, Ops, Product, and Finance; steward data quality; and contribute to QA across the analytics lifecycle. Office-based role requiring strong collaboration and technical precision.

Qualifications

  • Bachelor’s degree in Computer Science, Data Analytics, Information Systems, or a related quantitative field.

Responsibilities

  • Design, build, and maintain Power BI semantic models on analytics-ready data assets; manage relationships, DAX, calculation logic, and Row-Level Security.
  • Steward the single source of truth for metric and KPI definitions across reports, self-serve queries, and AI agents.
  • Optimize semantic models for accuracy, performance, and scalability; collaborate with Data Engineers to support the semantic layer.
  • Engage cross-functional stakeholders to gather requirements and define trusted KPIs.
  • Translate business questions into modelled data solutions with consistent business rules.
  • Create and manage user stories on the Azure DevOps board with clear requirements and acceptance criteria.

Skills

BI Development
Analytics Engineering
Power BI
DAX programming
Data Governance
SQL
Snowflake
dbt
Medallion Architecture
Azure DevOps
Jira
Salesforce
D365 CRM

Education

Bachelor’s degree in Computer Science, Data Analytics, Information Systems, or related quantitative field

Tools

Snowflake
Azure DevOps
Jira
dbt
Power BI
Salesforce
D365 CRM

Job description

SMART Technologies is seeking a Data Solutions Specialist to connect business needs with data engineering and reporting. You will design semantic models, govern KPI definitions, and ensure trustworthy data foundations for reports, self-serve analytics, and AI.

You will collaborate with Sales, Ops, Product, and Finance; steward data quality; and contribute to QA across the analytics lifecycle. Office-based role requiring strong collaboration and technical precision.

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