Sr Data QA Engineer

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 clear 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

Work arrangement
No