About the Role:

We are seeking an experienced Senior Quality Assurance Engineer - Data & AI with strong expertise in ETL, Data Warehouse, and Big Data Testing to ensure the quality, reliability, and integrity of enterprise Data & AI solutions. The ideal candidate will have hands-on experience validating complex data ingestion pipelines, transformation logic, cloud-based data platforms, and analytics solutions built on technologies such as Microsoft Fabric, Databricks, Azure Data Factory, and modern Big Data ecosystems.

This role requires a quality leader who can define testing strategies, validate enterprise-scale data platforms, collaborate directly with customers, and mentor junior QA engineers while remaining hands-on in testing activities whenever required.

Key Responsibilities

Data & ETL Testing

- Design, develop, and execute comprehensive test strategies for enterprise Data Engineering, Data Warehouse, and Analytics solutions.
- Validate ETL/ELT pipelines, data ingestion frameworks, transformation logic, and end-to-end data movement across multiple systems.
- Verify data quality, completeness, accuracy, reconciliation, and business rule implementation.
- Perform source-to-target data validation and ensure consistency across enterprise data platforms.
- Test batch, incremental, and near real-time data processing pipelines.

Big Data & Cloud Platform Testing

- Validate solutions built on Microsoft Fabric, Databricks, Azure Data Factory (ADF), Azure Synapse, or similar Big Data platforms.
- Test Lakehouse, Data Warehouse, and cloud-native analytics solutions.
- Validate large-scale structured,



semi-structured, and unstructured datasets.
- Perform SQL-based validation and data profiling across enterprise datasets.
- Ensure data security, governance, and compliance requirements are met.

Quality Strategy & Test Management

- Develop test strategies, test plans, test scenarios, and detailed test cases for enterprise data projects.
- Create risk-based testing approaches aligned with business priorities.
- Track testing progress and publish quality metrics, dashboards, and test execution reports.
- Manage defect lifecycle, root cause analysis, and quality improvements.
- Support User Acceptance Testing (UAT) and production validation activities.

Leadership & Stakeholder Collaboration

- Lead testing activities across multiple workstreams while remaining an individual contributor when required.
- Mentor and guide junior QA engineers on testing methodologies and best practices.
- Collaborate with Business Analysts, Data Engineers, AI Engineers, Architects, and Product Owners.
- Communicate effectively with client stakeholders and participate in solution walkthroughs and status meetings.
- Drive continuous improvement of QA processes and enterprise testing standards.

Roles and Responsibilities





Ideal Candidate Profile

- 6–10 years of experience in Software Testing with a robust focus on ETL, Data Warehouse, and Big Data Testing.
- Proven experience testing enterprise Data Engineering solutions.
- Strong expertise in:
- ETL/ELT Testing
- Data Warehouse Testing
- Data Migration Testing
- Data Validation & Reconciliation
- SQL & Database Testing
- Functional & Regression Testing

- Hands-on experience with one or more of:

- Microsoft Fabric
- Databricks
- Azure Data Factory (ADF)
- Azure Synapse
- Informatica
- Talend
- SSIS

- Strong SQL skills with experience validating complex transformation logic and source-to-target mappings.

- Experience creating:
- Test Strategy
- Test Plan
- Test Cases
- Test Execution Reports
- Defect Reports
- Quality Dashboards

- Familiarity with API testing using Postman or similar tools.
- Experience with Azure DevOps, Jira, Git, and Agile/Scrum delivery methodologies.
- Excellent communication and stakeholder management skills.
- Experience leading small QA teams while remaining hands-on in delivery.

Preferred Qualifications

- Bachelor's or Master's degree in Computer Science, Information Technology, Engineering, or related field.
- ISTQB Foundation/Advanced Certification preferred.
- Microsoft Azure Fundamentals (AZ-900) or Data certifications are advantageous.
- Exposure to automation testing using Selenium, Playwright, or similar frameworks.
- Experience testing AI, Analytics, or Business Intelligence solutions is a plus.

📌 Senior Quality Assurance Engineer - Data & AI (Mumbai)
🏢 Exponentia.AI Private
📍 Mumbai