About The Role

We're looking for a QA Engineer to own quality assurance for our data engineering projects, while also providing QA support across other project teams as needed. You'll work closely with data engineers to validate pipelines and data products, and step in on functional testing for web and app projects when required. This role is ideal for someone who is detail-oriented, comfortable working with data at scale, and able to juggle priorities across multiple teams.

Responsibilities
Validate data pipelines end-to-end: source-to-target checks, transformations, data completeness, accuracy, and reconciliation
Write and execute SQL queries to test data quality across ETL/ELT workflows
Design and maintain test plans, test cases, and traceability documentation for data projects
Build automated data quality checks and integrate them into pipeline workflows
Test reports and dashboards (e.g., Power BI/Tableau) against source data to verify metrics and business logic
Perform smoke, regression, and integration testing after pipeline deployments and schema changes
Support functional, regression, and UAT testing on other projects (web/app) when required
Log, track, and verify defects; work closely with data engineers and developers through resolution




Participate in requirement reviews to identify testability gaps and edge cases early
Contribute to improving QA processes, standards, and documentation across teams

Requirements
Experience testing data pipelines, ETL, or data warehouse projects
Solid SQL skills — able to write complex queries for data validation independently
Understanding of data warehousing concepts (schemas, transformations, incremental loads, slowly changing dimensions)
Experience with test management and defect tracking tools (e.g., Jira)
Ability to read and understand pipeline logic and data models to design meaningful tests
Strong attention to detail and ability to switch context across multiple projects
Valuable communication skills for working with cross-functional teams
Exposure to Agile/Scrum ways of working

Nice to Have
Experience with Azure data services (Azure Data Factory, Synapse, ADLS)
Hands-on experience with Databricks (notebooks, Delta Lake, job runs)
Test automation skills — Python, pytest, or data quality frameworks like Excellent Expectations or dbt tests
Experience testing APIs (e.g., Postman) or basic web automation (e.g., Selenium/Playwright)
Familiarity with CI/CD pipelines (e.g., Azure DevOps, GitHub Actions)

📌 Qa Engineer Data Engineering Bangalore East (India)
🏢 Phigital Care
📍 India