• Design, implement, and maintain automated data quality checks to validate accuracy, completeness, consistency, and timeliness across data pipelines and analytics layers. • Implement proactive monitoring and alerting for data pipelines to detect anomalies, schema changes, or data drift. • Validate business logic, calculations, aggregations and filters in BI tools to ensure alignment with business definitions. • Perform end-to-end testing of data pipelines, including ingestion, transformation (ETL/ELT), semantic layers and reporting outputs. • Conduct regression testing for schema changes, pipeline updates, and BI model modifications. • Integrate data quality checks into CI/CD pipelines and production monitoring. • Monitor data freshness, volume, and distribution to proactively detect and alert on failures or quality degradation. • Partner with data engineering, analytics, and product teams to define data acceptance criteria and quality thresholds.