ETL Test Lead

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

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.

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