Owns quality of data from source systems through ETL/ELT into BigQuery and the Looker reporting layer. Also covers functional and API testing of surrounding services. Embedded in an Agile/Scrum team with Data Engineers and Analysts.

The role is not limited to a single stream. Depending on delivery priorities the person will work across different projects, including Data & Reporting (primary focus), Web and eCommerce, and other platform initiatives. We expect flexibility: switching context between projects, ramping up on an unfamiliar domain quickly, and applying the same structured test approach regardless of which system is under test.

Responsibilities

- Define and run data quality checks: counts, completeness, nulls, duplicates, referential integrity, field-level reconciliation, KPI and business rule validation.
- Reconcile source vs. target during migrations; find root cause of discrepancies.
- Validate ETL/ELT logic and the dashboards/KPIs built on top of it.
- Test APIs and integrations that feed or consume data.
- Own the defect lifecycle end to end with Data Engineers.
- Contribute to test strategy, UAT and release readiness.
- Test design (core of the role)
- Turn business and reporting requirements into clear test scenarios, test cases and checklists. This is a daily activity, not documentation done after the fact.




- Maintain test artefacts in Jira / Xray so results are traceable and repeatable by others.
- Build and own a smoke suite for data pipelines and reports: run after each deployment or pipeline release to confirm data loads, key tables are populated and critical KPIs are not broken.
- Build and maintain a regression suite covering reconciliation checks, business rules and key dashboards; keep it lean and prioritized by risk, and extend it with every confirmed defect.

Must have

- Primary focus is Quality/Testing. The individual will be working with data/SQL, candidate should primarily be a QA/Test Engineer with additional data experience.
- 6 to 8 years of experience, 5+ years in testing, 1-2 years of them in data/BI/analytics.
- Confident with SQL: comfortable writing joins and aggregations and comparing datasets independently.
- Practical experience with data quality checks, reconciliation and validation of migrated data.
- Working understanding of data models, schemas and dependencies; structured and semi-structured data.
- Independent test design (scenarios, cases, checklists) and explicit defect documentation.
- Experience building and maintaining smoke and regression coverage.
- Agile/Scrum and Git-based workflows.
- Good analytical and root-cause skills.

If the role excites you, Please apply through this link: https://bhartiyaconverge.app.param.ai/jobs/sr-data-qa-engineer

📌 Sr Data QA Engineer (Bengaluru)
🏢 Bhartiya Converge
📍 Bengaluru