Data Quality Engineer

Design and implement automated test scripts to validate ETL workflows, data pipelines, and data transformation logic across large datasets and cloud platforms (Azure, AWS, GCP).

Build reusable and scalable test automation frameworks using Python and SQL, integrating tests into CI/CD pipelines to support continuous testing and delivery.

Collaborate with data engineers, analysts, and stakeholders to align test strategies with data quality standards and participate in Agile ceremonies for iterative delivery.

4-6 years of professional experience in data quality engineering with expertise in ETL automation and Data Warehouse/Data Lake testing.

Strong proficiency in SQL for data validation and test automation; hands-on experience with Python scripting and framework development.

Practical experience with test automation frameworks and working knowledge of cloud data services (Azure Data Factory, Azure Databricks, AWS Glue, Lambda, Redshift, GCP BigQuery).

Familiarity with CI/CD tools (Jenkins, Git, Azure DevOps) and Agile/Scrum methodologies.

Experienced in cross-cloud data platforms with hands-on automation capabilities and integration of tests into CI/CD workflows for scalable delivery.

Demonstrates operational ownership by embedding data quality checks within complex data pipelines and collaborating closely with multi-disciplinary teams.

Comfortable working in Agile environments and contributing actively to sprint planning, retrospectives, and iterative process improvements.