Improvement Team. The successful respondent will be responsible for establishing, maturing, and sustaining a formal QA function for Power BI reports, dashboards, data models, and related analytics products that support business operations, regulatory compliance, resource planning, and performance management. The services will include the development and implementation of QA standards, templates, methodologies, quality gates, and release governance processes to ensure reporting solutions are accurate, reliable, traceable, auditable, and suitable for business use.

Responsibilities

- Develop and execute test strategies, plans, and cases for Power BI solutions, while maintaining QA standards, regression test suites, release checklists, and other core QA deliverables that support consistent, reliable, and business-ready reporting for operational, compliance, resource planning, and performance management purposes.
- Perform functional testing and regression testing across all analytics components to confirm reporting solutions remain reliable for business operations, compliance reporting, resource optimization, and KPI monitoring.
- Ensure end-to-end data validation, including source-to-report accuracy, to confirm that reporting outputs support operational decisions, regulatory and compliance reporting, resource planning, and KPI measurement and optimization.
- Establish and enforce a formal QA gate prior to release to support reliable business reporting, compliance readiness, and controlled deployment of operational analytics.
- Identify, document, prioritize, and track defects and issues using standard tools (e.g., DevOps or equivalent)
- Collaborate with developers to ensure timely resolution of defects




- Validate fixes and confirm issues are resolved before production deployment
- Validate data integrity and consistency across shared Power BI models and downstream reports to support accurate operational reporting, compliance requirements, resource planning, and KPI analysis.
- Assess the impact of changes to data models on dependent reports and dashboards, including potential effects on operational decision-making, regulatory compliance, resource planning and KPI reporting.
- Ensure high standards of data accuracy, completeness, consistency, and traceability to support operational decision-making, regulatory compliance, audit readiness, resource allocation, and business performance reporting.
- Standardize QA practices and introduce repeatable testing frameworks and regression coverage to improve reporting reliability, reduce rework, and support efficient use of business and technical resources.
- Identify opportunities to improve testing efficiency, reduce rework, optimize resource use, and support more predictable delivery of reporting solutions that enable effective business operations and performance management.
- Review business requirements, user stories, acceptance criteria, and reporting specifications to ensure they are complete, clear, testable, and aligned with operational, regulatory, compliance, resource planning, and KPI reporting requirements.




- Validate that dashboards and reports accurately reflect approved business rules, operational processes, regulatory obligations, resource planning assumptions, and key performance indicators used to monitor service delivery and business performance.
- Support continuous improvement of business operations by identifying data quality, process, control, or reporting gaps that may affect compliance, resource allocation, operational efficiency, or KPI performance, and recommending mitigation or improvement opportunities.
- Identify and recommend opportunities for test automation, reusable validation scripts, and process improvements to support standardized and efficient QA practices.
- Develop and maintain reusable test assets, including regression test suites and data validation scripts, to improve testing consistency and coverage.

Qualifications

- Data validation and testing methodologies
- SQL and data querying
- Data modeling concepts (semantic models, relationships, measures)
- Experience with test management and defect tracking tools (e.g., Azure DevOps, Jira)
- Experience validating data from SQL Server, ETL pipelines, semantic models, and Power BI reports.
- Experience with data profiling and data quality assessment
- Understanding of DAX (Data Analysis Expressions) for validating measures and calculations
- Robust understanding of Star schema & snowflake schema design
- Strong attention to detail with the ability to identify data inconsistencies and anomalies
- Ability to assess downstream impacts of data/model changes
- Structured and methodical approach to testing and validation.
- Additional preferred qualifications:
- Power Query(M)

📌 Quality Assurance (Burnaby)
🏢 Affinity
📍 Burnaby