Role Overview
We are looking for an experienced QA Fabric Specialist to ensure data quality, validate analytical solutions, and define testing strategies within the Microsoft Fabric ecosystem. The role requires deep expertise in data platforms, white-box testing, and close collaboration with Data Engineering, BI, and business stakeholders.
Must Have
Experience
- 8+ years of experience in Data Engineering, Business Intelligence, or Data QA (Senior / Principal level).
Microsoft Fabric
- Hands-on experience with Microsoft Fabric
- (at least one commercial project or a substantial POC).
Core Microsoft Stack
- 5+ years of combined experience with:
- Azure Synapse
- Azure Data Factory (ADF)
- SQL Server
Coding / SQL
- Expert-level SQL skills.
- Ability to write complex manual validation queries for data quality checks.
Testing Approach
- Proven experience in white-box testing
- (testing data pipelines, transformations, and codenot just UI).
Testing Strategy
- Ability to define a test strategy from scratch, including:
- Master Test Plan
- Test environments and data strategy
Should Have
Experience
- 10+ years of total professional experience.
Microsoft Fabric
- Strong understanding of:
- DirectLake vs Import mode
- OneLake shortcuts
Core Microsoft Stack
- Experience migrating legacy SQL Data Warehouses to Azure.
Coding
- Proficiency in Python and/or PySpark.
- Ability to write test scripts in notebooks.
Automation & DevOps
- Experience setting up automated data quality gates in Azure DevOps.
Business Collaboration
- Experience coordinating User Acceptance Testing (UAT) with business stakeholders.
Nice to Have
Experience
- Previous experience as a Solution Architect.
Certifications
- Microsoft Certified: Fabric Analytics Engineer Associate (DP-600).
Data Governance
- Experience with Microsoft Purview.
Automation Skills
- Experience using C# or PowerShell for automation.
Data Testing Frameworks
- Experience with:
- Great Expectations
- dbt testing
Monitoring & Reporting
- Ability to create Data Quality Dashboards to continuously monitor data health.
