Title: Senior QA Engineer – Microsoft Fabric / AI / Data Analytics
Location: Bangalore (Hybrid)
Experience: 8 –12 years
Key Responsibilities:-
1. QA Strategy, Planning & Documentation
Define QA strategy for Microsoft Fabric–based data platform projects, including test scope, approach, timelines, and resource planning.
Create detailed test plans, test scenarios, and test cases for:
Data ingestion pipelines (Bronze → Silver → Gold layers)
Fabric notebooks, dataflows, and pipelines
Microsoft Purview integrations (lineage, cataloging, classifications)
AI-enabled Fabric features and Copilot workflows
Power BI dashboards and semantic models
Establish standard QA processes such as defect lifecycle, traceability matrices, and release readiness reporting.
2. Data Pipeline & Platform Testing
Validate data ingestion from multiple sources (e.g., OMS, SCADA, GIS, CIS, ABS, Partner systems).
Perform schema validation, reconciliation, and data quality checks across layers.
Conduct ETL/ELT testing, including:
Data completeness
Data accuracy
Performance validations
Error handling and retry logic
Verify audit/balance/control mechanisms in data pipelines.
Perform regression and integration testing for iterative sprints.
3. Power BI & Reporting QA
Validate dashboards and reports (including medium‑complexity multi‑source designs).
Test DAX logic, measures, filters, drill-downs, and visual accuracy.
Validate golden datasets and semantic models connected to the Fabric environment.
Ensure consistency in look‑and‑feel and UX standards.
4. AI, Copilot & Automation Validation
Test Copilot enablement features in Microsoft Fabric:
Prompt integration and responses
AI-driven dataflows
Automated model suggestions
AI enrichment and semantic extraction
Validate AI model performance, outputs, and alignment with security and compliance rules.
Automate repetitive test cases using tools such as:
PyTest / Python
PowerShell / Fabric REST API
Power BI Testing Frameworks
5. Environment, Security & Governance Validation
Validate RBAC implementation across workspaces and domains.
Confirm security propagation across Fabric objects.
Test compliance requirements and governance policies configured during the setup.
Validate Purview lineage accuracy.
6. UAT & Go‑Live Support
Support UAT cycles, defect triage, and priority management.
Work with SMEs to validate business use cases and reporting requirements.
Support Go‑Live readiness, documentation, post‑deployment validation, and hypercare.
Required Skills & Experience
Technical Skills
6–10+ years of QA experience in Data Platform / BI / Analytics projects.
Strong hands‑on QA experience in:
Microsoft Fabric (pipelines, dataflows, notebooks, lakehouses)
Power BI (datasets, semantic models, dashboards)
Azure Data services (Data Factory, Synapse, SQL, ADLS Gen2)
Strong SQL for deep data validation.
Familiarity with AI workflows and validation of LLM‑based features (Copilot preferred).
Experience testing ETL/ELT processes and data warehouse models (e.g., medallion).
Automation skills in Python, PyTest, PowerShell, or Fabric APIs.
Knowledge of DevOps pipelines, CI/CD, version control (Git/Azure DevOps).
Soft Skills
1.Strong analytical and problem‑solving ability.
2.Excellent communication skills for cross‑functional coordination.
3.Ability to lead QA efforts end‑to‑end with minimal supervision.
4.Strong documentation discipline and stakeholder reporting.
Nice-to-Have Skills
1.Experience validating Microsoft Purview lineage & metadata.
2.Understanding of AI prompt engineering concepts.
3.Exposure to cloud cost optimization testing for Fabric.
4.Experience validating SCADA/OMS/Utility datasets (aligned to your SOW).
5.ISTQB or equivalent certification.
