QA Automation Engineer; Power BI & Microsoft Fabric) Quality Assurance · Colombia, Costa Rica, Latam

WHAT WE DO

Founded in 2007, Growth Acceleration Partners (GAP) is a premier consulting and technology services company built for the AI era. We consult, design, build, and modernize revenue-generating software and data engineering solutions. By leveraging AI-native architectures, advanced data analytics, and deep modernization strategies, we help businesses secure a competitive advantage.

GAP’s remote, integrated engineering teams deliver end-to-end solutions that drive true business innovation. We are a woman-owned, Austin-based company with over 600 English-speaking engineers across Latin America and the U.S. Boasting industry-leading customer satisfaction scores, our core focus is the dual success of our clients and our people. We are a values-based organization deeply invested in the growth of our "GAPsters"—providing continuous education, onsite English classes, and cutting-edge training in AI, machine learning, and next-gen technologies to ensure our communities achieve long-term success.

We are seeking a detail-oriented Staff QA Automation Engineer with specialized expertise in Power BI testing and Microsoft Fabric migrations. This role is critical in ensuring data integrity, reliability, and high performance across our reporting and analytics environment. You will be responsible for a comprehensive testing strategy that combines front-end user experience validation using tools like Playwright with deep back-end data validation through SQL and data model checks.

• Bachelor’s Degree in Computer Science, Software Engineering, Data Science, or a related technical field.

• 8+ years of experience in Quality Assurance with a heavy focus on data-centric applications and reporting environments.

• Proven track record in Power BI Service testing, including the validation of navigation, permissions, and report usability.

• Strong experience in back-end data validation, including querying SQL databases and troubleshooting complex data pipelines.

• Experience working in Microsoft Fabric or Azure environments, specifically handling data migrations and environment comparisons.

• Demonstrated ability to design and manage automated testing processes for data integrations.

• Proven experience leveraging AI-powered development/testing tools (such as Claude Code, Cursor, or Git Hub Copilot) to accelerate test script creation and complex data verification.

• Develop and implement comprehensive QA strategies for data workflows, pipelines, and semantic models within Microsoft Fabric.

• Execute front-end testing of Power BI Service functionality, ensuring seamless user interactions and report consistency.

• Perform back-end validation by querying SQL sources to confirm the accuracy of data transformations and performance metrics.

• Compare legacy systems against Fabric environments to ensure functional parity and identical data results.

• Design, manage, and maintain automated testing frameworks for pipelines and integrations to ensure long-term scalability.

• Conduct root cause analysis for complex data issues and coordinate with developers and engineers to resolve quality bottlenecks.

• Track and report on quality metrics and SLAs to ensure data availability and accuracy standards are consistently met.

• Reporting & BI: Expertise in Power BI Service (navigation, permissions, usability) and semantic models.

• Data Validation: Advanced SQL querying for back-end testing and data transformation validation.

• Automation: Hands-on experience with Playwright for front-end automation and knowledge of automated testing for data pipelines.

• Environment: Proficiency in Microsoft Fabric and Azure ecosystems.

• Analysis Tools: High level of comfort with Excel (pivot tables, lookups) for comparative data analysis.

• Data Principles: Deep understanding of data quality principles including completeness, accuracy, and consistency.

• AI & Advanced Tools: Experience utilizing AI-assisted testing frameworks (e.g., AI-driven test generators) or validating data models impacted by AI/ML workflows.

• Hands-on experience with agentic AI workflows, prompt engineering for QA, or evaluating…