Must have experience in Databricks and Python

Key Responsibilities

Data quality ownership
- Define, implement, and maintain data quality rules across ingestion, transformation, and reporting layers, selecting appropriate failure behaviour (warn, filter, or fail) based on business impact
- Identify gaps in existing DQ coverage - particularly for sources and vendor-specific outputs that have no constraints defined - and prioritise them with the engineering team
- Review and challenge rules that silently drop or filter records, ensuring upstream data issues are surfaced rather than hidden

Testing
- Write and maintain automated regression tests for business-critical reports, using seeded input data and expected output comparisons so defects are caught before deployment
- Write contract tests that enforce the schema and structure of pipeline outputs, failing the build when an upstream change breaks a downstream report
- Build and maintain representative test datasets that cover edge cases - nulls, multi-entity data, CDC sequences - for use across the test suite




- Ensure tests cover all recent pipeline features and SQL logic before they are merged

CI/deployment quality gates
- Add automated data assertions to the deployment pipeline so that a pipeline that produces incorrect or empty outputs is blocked from reaching production
- Define and maintain per-report baselines (expected row counts, key aggregates, permitted variance) and encode them as automated checks that run on every deployment

Defect management
- Reproduce data issues reported by users as failing tests before any fix is applied, building a regression library from real incidents
- Collaborate with report users and business stakeholders to translate business-level data quality observations into concrete, automatable assertions

Team practice
- Review pull requests that touch transformation logic or data quality rules, blocking merges where critical business logic is untested
- Maintain the team's testing stra

📌 Data Quality Analyst (India)
🏢 Careerwise
📍 India