We run a multi-client analytics pipeline delivering BI-ready data to clients across e-
commerce and advertising platforms. This role owns quality assurance across the pipeline — from automated testing to data certification before it reaches dashboards.
- Responsibilities
Automation
- Build and maintain automated test suites covering data pipelines end-to-end
(build, transform, delivery stages)
- Develop reusable QA frameworks/scripts to reduce manual validation effort across clients
- Integrate quality checks into CI/CD so regressions are caught pre-merge, not post-deploy
- Automate recurring reconciliation checks (source vs. output row counts, metric totals, freshness)
Data Quality Testing
- Design and implement data quality tests: uniqueness, referential integrity,
null/completeness checks, accepted-value ranges, freshness SLAs
- Validate current features/models against production data before release
- Investigate and triage test failures — distinguish genuine data quality issues from pipeline/build failures
- Maintain test coverage documentation and flag gaps as new data sources/clients onboard
Data Certification
- Own the certification process for new client onboarding and new model releases
— sign-off before dashboards go live
- Define and enforce certification checklists (schema validation, metric reconciliation vs. source, historical trend sanity checks)
- Partner with data engineers to resolve certification blockers
- Maintain an audit trail of certification decisions for compliance/traceability
Cross-functional
- Work closely with data engineers to translate QA findings into actionable fixes
- Communicate data quality risks and certification status clearly to stakeholders
- Contribute to continuous improvement of QA standards and best practices across the team
- Requirements
- 6+ years in QA/data quality roles, with hands-on SQL experience
- Experience testing data pipelines/ETL systems (any modern stack)
- Familiarity with data testing frameworks (e.g., dbt tests, Great Expectations, or similar)
- Strong analytical skills — able to reconcile metrics and spot anomalies in large datasets
- Excellent written communication for certification documentation and stakeholder updates
- Nice to have
- Experience with cloud data warehouses (BigQuery/Snowflake/Redshift)
- Exposure to workflow orchestration tools (Airflow or similar)
- Prior experience in e-commerce/advertising analytics domains