Lead QA Engineer / ETL

Job Title: QA Engineer ETL Testing, Data & AI Platforms

Location: Bangalore/Chennai/Hyderabad/Nagpur/Pune

Hybrid Work Model

Experience

6-10+ Years

Job Summary

We are seeking a highly skilled QA Engineer with extensive experience in ETL Testing across complex, multi-platform enterprise architectures. The ideal candidate will have strong expertise in validating large-scale data integrations involving DB2, Salesforce, SAP, Snowflake, Power BI, Data Lakes, AI-driven solutions, and Python-based data pipelines.

The role requires a quality-focused professional capable of ensuring data accuracy, integrity, completeness, and performance across various enterprise systems while supporting modern analytics and AI initiatives.

Key Responsibilities

• Design, develop, and execute comprehensive test strategies for ETL and data integration programs.
• Validate end-to-end data movement across multiple source and target systems including DB2, Salesforce, SAP, Snowflake, and Data Lakes.
• Perform data quality, data reconciliation, transformation, and data validation testing.
• Develop and execute SQL queries to validate complex data transformations and business rules.
• Collaborate with Data Engineers, Business Analysts, AI/ML teams, and Product Owners to understand requirements and define testing approaches.
• Validate AI and analytics datasets used for machine learning and predictive modeling.
• Test and verify data visualizations, reports, and dashboards in Power BI.
• Automate testing processes using Python and relevant testing frameworks.
• Conduct performance, regression, integration, and system testing for data platforms.
• Identify, document, track, and resolve defects throughout the software development lifecycle.
• Support CI/CD processes and quality assurance best practices within Agile environments.
• Ensure compliance with data governance, security, and audit requirements.

Required Skills & Qualifications

ETL & Data Testing

• Strong experience in ETL/Data Warehouse Testing.
• Expertise in source-to-target validation and data reconciliation.
• Experience validating complex data transformation rules and business logic.
• Strong SQL skills and data analysis capabilities.

Enterprise Platforms

Hands-on testing experience with:

• DB2
• Salesforce
• SAP
• Snowflake
• Power BI

Data Engineering & Data Lakes

• Experience testing modern Data Lake architectures.
• Understanding of large-scale data ingestion, transformation, and analytics workflows.
• Experience with cloud-based data platforms is preferred.

AI & Advanced Analytics

• Experience testing AI-enabled applications and data pipelines.
• Understanding of machine learning data validation and model input/output verification.
• Knowledge of data quality requirements for AI/ML solutions.

Python

• Strong Python programming skills for test automation and data validation.
• Experience developing automated data quality and regression testing scripts.

Testing & Tools

• Test case design and execution.
• Defect management and tracking tools.
• API and data integration testing.
• Performance and regression testing.

Preferred Qualifications

• Experience with cloud platforms such as Azure, AWS, or GCP.
• Exposure to CI/CD pipelines and DevOps practices.
• Knowledge of data governance and master data management.
• Experience working in Agile/Scrum environments.
• Relevant certifications in QA, Data Engineering, Snowflake, or Salesforce are a plus.

Key Competencies

• Strong analytical and problem-solving skills.
• Excellent attention to detail.
• Ability to work in complex enterprise environments.
• Strong stakeholder communication and collaboration skills.
• Ability to manage multiple priorities in a fast-paced setting.

Nice to Have

• Experience with AI/ML testing frameworks.
• Knowledge of Data Mesh or modern data architecture principles.
• Exposure to Generative AI solutions and validation methodologies.
• Experience with automated testing tools and frameworks.