Job Description : Microsoft Fabric & Power BI Data QA / Test Engineer

Artificial Intelligence & Engineering

AI & Engineering leverages cutting-edge engineering capabilities to help build, deploy, and operate integrated/verticalized sector solutions in software, data, AI, network, and hybrid cloud infrastructure. These solutions insights are powered by engineering for business advantage, helping transform mission-critical operations.

We are seeking an experienced Microsoft Fabric & Power BI Data QA / Test Engineer with 3 - 8 years of experience in end-to-end data quality engineering, pipeline validation, and business intelligence (BI) testing. You will design comprehensive test strategies spanning data ingestion in Microsoft Fabric through to semantic modeling and dashboard reporting in Power BI. The ideal candidate combines hands-on testing expertise in Microsoft Fabric, extensive SQL skills, and PySpark scripting with strong, hands-on experience in testing Power BI reports, DAX measures, semantic models, and Row-Level Security (RLS).

Position Summary

Experience : 3 - 8 years

Role : Quality Assurance Engineer - Microsoft Fabric & Power BI / Data Analytics Platform

As a Fabric & Power BI Data QA Engineer, you will ensure the end-to-end data accuracy, reliability, and visualization integrity of enterprise analytics solutions. You will collaborate with data engineers, BI developers, analysts, onsite/offshore teams, and business stakeholders to validate data transformation logic, data pipeline orchestration, semantic models, and executive reporting dashboards.

Work You'll Do :

- End-to-End Test Strategy & Planning : Review functional and technical specifications to create comprehensive test plans covering the entire data lifecycle - from source ingestion to final Power BI reporting.

- Fabric Pipeline & Data Layer Testing : Validate source-to-target data mappings, incremental loads, watermarking, schema drift handling, and business transformations across OneLake, Lakehouse (Delta tables), and Data Warehouse layers.

- Power BI & Semantic Model Validation : Thoroughly test Power BI reports and dashboards, validating semantic models, relationships, DAX calculations, filter contexts, KPIs, drill-throughs, and Row-Level Security (RLS).

- Automated & Script-Based Validation : Write and execute complex SQL queries and PySpark scripts within Fabric Notebooks to automate regression testing, aggregate checks, and cross-layer data reconciliation.

- Defect Management & Triage : Identify, document, log, and track data and visualization defects using Azure DevOps or Jira, working closely with engineering and BI teams for prompt resolution.

- Agile & Quality Governance : Actively participate in sprint planning, story refinement, and test estimation, driving QA standards and automated testing practices across the team.

The Team :

AI & Data offers a full spectrum of solutions for designing, developing, and operating cutting-edge Data and AI platforms, products, insights, and services. Our offering helps clients innovate and enhance their data and analytics capabilities, ensuring they make informed decisions backed by trusted, high-quality data and verified reporting.

AI & Data QA Professionals Will Work With Our Clients To :

- Define and execute test cases for end-to-end data and analytics solutions built on Microsoft Fabric and Power BI.

- Verify data accuracy and pipeline orchestration across Fabric Data Pipelines, Dataflows Gen2, and PySpark Notebooks.

- Validate data persistence and consistency across OneLake, Lakehouse, and Data Warehouse architectures.

- Perform rigorous Power BI Testing :

1. Reconcile report and dashboard metrics directly against underlying Fabric Lakehouse / Warehouse gold tables and source systems.

2. Validate complex DAX measures, calculated columns, hierarchies, and dynamic aggregation logic.

3. Verify report performance, slicers, cross-filtering behaviors, drill-downs, and visual interactions.

4. Test and validate Row-Level Security (RLS) and user access permissions across different security roles.

- Develop automated data validation scripts using SQL and PySpark for regression testing and large-volume reconciliation.

- Test pipeline error-handling frameworks, retry mechanisms, and schema drift handling.

- Integrate test gates and automated quality checks into Azure DevOps / CI/CD deployment pipelines.

Qualifications :

Must-Have Skills / Project Experience :

- 3 - 8 years of data testing/QA experience, with hands-on testing across modern data platforms and BI tools.

- Hands-on testing experience with Microsoft Fabric components : Lakehouse, Data Warehouse, OneLake, Dataflows Gen2, Data Pipelines, and Notebooks.

- Mandatory hands-on experience in Power BI Testing :

1. Validating semantic models, table relationships, and cardinality.

2. Verifying complex DAX measures, time-intelligence functions, and KPI logic.

3. Testing Row-Level Security (RLS), user role-based access, and dashboard performance.

4. Reconciling visual metrics against underlying SQL/Lakehouse datasets.

- Strong SQL proficiency to write complex validation queries, data reconciliation scripts, and aggregate comparisons.

- Hands-on experience using PySpark / Python for data validation and automated reconciliation.

- Solid understanding of dimensional data modeling (Star/Snowflake schemas) and ETL/ELT architecture.

- Experience in Agile environments with defect management tools (Jira, Azure DevOps) and version control (Git).

- Excellent analytical, problem-solving, documentation, and stakeholder communication skills.

Good-to-Have Skills / Certifications :

- Experience with automated data quality tools and frameworks (e.g., Great Expectations, PyTest, or automated BI testing tools).

- Experience with the broader Azure data platform (Azure Data Lake, Azure Data Factory, Synapse Analytics).

- Microsoft certifications : DP-600 (Fabric Analytics Engineer Associate), PL-300 (Power BI Data Analyst), or DP-203 (Azure Data Engineer).

- Domain knowledge in Relocation Management or professional services.