ETL Test Lead

Job Description: esting Skills

• Data Testing
• ETL/ELT Testing
• System Integration Testing (SIT)
• User Acceptance Testing (UAT)
• Regression Testing
• Defect Management

Data Technologies

• SQL
• DBT Testing Framework
• BigQuery
• Data Validation Techniques
• Reconciliation Testing

SAS Knowledge

• SAS Datasets
• PROC SQL
• SAS Reports
• SAS Data Validation Concepts

Tools

• Jira
• Azure DevOps
• Git
• Test Management Tools

Cloud Platforms

• Google Cloud Platform (GCP)
• BigQuery
• Cloud Storage

Responsibilities: Data Migration Testing

• Validate migrated data from SAS to GCP platforms.
• Perform source-to-target data validation and reconciliation.
• Verify completeness, accuracy, and consistency of migrated data.
• Execute historical and incremental data validation testing.

ETL/ELT Testing

• Test DBT transformation pipelines and business rules.
• Validate data movement across Bronze, Silver, and Gold layers.
• Verify joins, aggregations, calculations, and derived attributes.
• Ensure transformation logic matches SAS outputs.

Data Quality Validation

• Validate data quality rules and controls.
• Identify duplicates, null values, data type mismatches, and referential integrity issues.
• Perform anomaly detection and exception analysis.
• Support implementation of automated data quality checks.

Test Planning & Execution

• Create test plans, test scenarios, and test cases.
• Prepare test data and execute SIT, UAT, regression, and production validation testing.
• Track and manage defects through closure.
• Support release and deployment validation activities.

Reconciliation & Reporting

• Perform record count, field-level, and aggregate-level reconciliation.
• Compare SAS results with GCP outputs.
• Produce reconciliation reports and defect summaries.
• Support business and regulatory sign-off activities.

Collaboration

• Work closely with Data Engineers, DBT Developers, SAS SMEs, Data Architects, and Business Analysts.
• Participate in Agile ceremonies and sprint activities.
• Support stakeholder reviews and testing sign-offs.

Qualifications: Graduate in Computer Science, Data Science, Information Technology, or a related field. 6-8 years of experience in data quality or data management.