Join our Testing Services team as an ETL Technical Specialist, bringing your expertise in ETL testing and SQL-based data validation to ensure the integrity of our data flows. This role is crucial for maintaining high standards in our data transformation and reconciliation processes across various source systems and SPM platforms.

You will play a vital role in validating complex data pipelines, ensuring accuracy and consistency from extraction to loading. Your contributions will directly impact the reliability and quality of our data solutions.

Validate data extraction, transformation, and loading processes, meticulously reviewing source-to-target mappings and transformation logic. Execute various load tests, including full, incremental, delta, and historical loads, while validating all transaction types like insert, update, delete, and effective-dated changes.

Ensure seamless data movement across all system layers (source, staging, warehouse, target) by writing advanced SQL queries for backend validation. Conduct comprehensive table, column, and record-level validations, alongside detailed data reconciliation between source and target systems to identify and resolve discrepancies.

Proactively identify and investigate data anomalies, duplicates, and missing records. Execute robust data quality checks, pinpointing and logging defects throughout the testing lifecycle. Collaborate closely with Development, ETL, Product, and Business teams to resolve issues, and prepare essential test evidence to support release sign-off activities.

A motivated QA/Test Engineer with 6-8 years of experience in ETL Testing and strong SQL-based data validation skills is required. The ideal candidate will possess a deep understanding of data flow validation, business rules, and reconciliation across multiple source systems.

Proficiency in writing SQL queries for backend validation, performing detailed data comparisons at various levels (table, column, record), and conducting end-to-end data reconciliation is essential. Experience in investigating data anomalies and executing data quality checks is also crucial for success in this role. Active participation in defect triage and close collaboration with cross-functional teams are expected.