Summary:

We are seeking a meticulous ETL QA Engineer to ensure data integrity across our Databricks platform. You will validate complex data pipelines using SQL and Python, working closely with global teams to deliver high-quality data solutions. This role requires flexibility to ensure overlap with US EST working hours for real-time coordination and team collaboration.

Key Responsibilities:

- Design, develop, and execute ETL test cases to validate data extraction, transformation, and loading processes.

- Write and execute complex SQL queries to perform data validation between multiple hops.

- Medallion Architecture Testing: Validate data integrity as it moves through the Bronze, Silver, and Gold layers within Databricks.

- Write and execute advanced SQL and Python scripts to validate large datasets and identify defects.

- Design, develop, and execute UI Front end manual test cases to validate the functionalities of the software.

- Identify, document, and track defects, collaborate with developers to ensure timely resolution.

- Participate in project meetings and be available for discussions in US EST working hours as needed.

Required Skills & Qualifications:

Must-have:

- Advanced SQL: Proficiency in windows functions, complex joins and CTEs for deep data validation.

- ETL & DWH: Deep understanding of ETL and Data Warehouse concepts.

Good to have:

- Databricks Experience: Hands-on experience with Databricks Notebooks and cluster management.

- Programming: Strong skills in Python, specifically PySpark and Pandas for large-scale data manipulation.

- Cloud Platform Familiarity: Experience working within Azure or AWS environments.

- Agile Methodologies and Defect Tracking Tools: Experience with Jira for defect tracking and working with Agile/Scrum framework.

- CI/CD (Additional Plus): Familiarity with automated deployment pipelines and version control (Git).