Senior Specialist - Quality Engineering

• The role focuses on ensuring reliable data movement automated validation data quality and operational visibility across endtoend data pipelines
• Perform endtoend data pipeline validation covering sourcetotarget data flow and transformation accuracy
• Design and maintain automated E2E test frameworks for data pipelines and ETLELT 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 datavalidation testing and integrate tests into CICD pipelines
• Perform observability validation including pipelinejob health data freshness volume schema anomalies s and monitoring dashboards
• Validate monitoring and ing 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 dataquality 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 ETLELT Validation Data Reconciliation Data Observability Amazon CloudWatch CICD RCA

Mandatory Skills : AI/ML Testing, Cloud testing