Senior Quality Assurance Engineer

• About the role

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 new 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

Skills

DBT/SQ