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 up-to-date data architecture principles.
- Exposure to Generative AI solutions and validation methodologies.
- Experience with automated testing tools and frameworks.

📌 Lead QA Engineer / ETL (Bengaluru)
🏢 Perficient
📍 Bengaluru