We are seeking a skilled and experienced Data Quality Engineer (Data QE) to join our team. The ideal candidate will have a strong background in Quality Engineering, ETL and database testing, and hands-on expertise with Python, PySpark, SQL, and Databricks. You will be responsible for designing and executing tests to ensure the quality and reliability of data pipelines and analytics platforms.

Key Responsibilities :

- Design and implement end-to-end test strategies for data pipelines and ETL processes.

- Conduct thorough ETL and database testing to ensure data accuracy, completeness, and consistency.

- Develop automation frameworks and scripts using Python and PySpark.

- Perform data validation and integrity checks using advanced SQL queries.

- Work with big data platforms such as Databricks for testing and validation.

- Collaborate closely with data engineers, analysts, and product teams to understand data requirements.

- Identify data quality issues, troubleshoot, and work with stakeholders to resolve them.

- Document test cases, results, and provide regular status updates.

Mandatory Skills & Experience :

- 6+ years of experience in Quality Engineering and QE processes.

- 23 years of hands-on experience in ETL testing and database testing.

- 23 years of experience with Python and PySpark for data testing and automation.

- 23 years of experience in writing complex SQL queries for data validation.

- Experience working with Databricks or similar big data platforms.

Preferred Qualifications :

- Experience with cloud data platforms (e.g., AWS, Azure, GCP).

- Familiarity with CI/CD pipelines and test automation tools.

- Knowledge of data governance and data quality frameworks.

Education : Bachelors or Masters degree in Computer Science, Information Systems, or a related field.