Senior Specialist - Quality Engineering

• Ensure reliable data movement by managing automated validation, data quality, and operational visibility across end-to-end data pipelines.
• Perform end-to-end data pipeline validation, covering source-to-target data flow and transformation accuracy.
• Design and maintain automated E2E test frameworks for data pipelines and ETL/ELT processes.
• Implement data quality checks for completeness, accuracy, consistency, uniqueness, validity, and timeliness.
• Validate business rules, reconciliation results, schema changes, and data transformations across pipeline layers.
• Automate regression and data-validation testing, and integrate tests into CI/CD pipelines.
• Conduct observability validation, including pipeline/job health, data freshness, volume metrics, schema anomalies, and monitoring dashboards.
• Validate monitoring and alerting using tools such as Amazon CloudWatch where applicable.
• Investigate data discrepancies and pipeline failures; perform Root Cause Analysis (RCA) and coordinate defect resolution with Data Engineering teams.
• Document test scenarios, test results, defects, data quality metrics, and validation evidence.
• Work closely with Data Engineers, Data Quality Governance, and Platform teams to ensure stable and trustworthy data pipelines.

Key Skills

Data Pipeline Testing E2E Testing Test Automation Data Quality SQL ETL/ELT Validation Data Reconciliation Data Observability Amazon CloudWatch CICD RCA

Mandatory Skills : AI/ML Testing, Cloud testing