Your Qualifications: Bachelors degree in Computer Science, Information Systems, Data Engineering, Software Engineering, or related technical field; Masters degree preferred 5+ years of progressive experience in data quality engineering, QA engineering, or test automation with focus on data systems and APIs Demonated track record of implementing comprehensive testing frameworks for enterprise-scale data platforms and APIs Proven experience testing complex data pipelines, integrations, and RESTful APIs in production environments Core Testing Competencies: Expert-level experience with API testing tools and frameworks (Postman, REST Assured, SoapUI, JMeter, Swagger/OpenAPI) Strong proficiency in SQL for data validation, query testing, and database verification across large datasets Advanced Python programming skills for test automation, data validation scripts, and custom testing tools (pytest, unittest) Experience with data quality testing tools (Great Expectations, Soda Core, dbt tests, or similar) Strong understanding of ETL/ELT testing methodologies and data pipeline validation techniques Knowledge of test automation frameworks and CI/CD integration (Selenium, Jenkins, GitLab CI, GitHub Actions) Experience with performance testing and load testing tools for APIs and data systems (JMeter, Gatling, Locust). Platform and Technology Experience: Hands-on experience testing in cloud platforms (AWS, Google Cloud Platform, or Azure) 2+ years of experience with Snowflake ecosystem, including testing SnowPipes, Streams, Views, stored procedures, and data models Experience with AWS services testing (S3, Lambda, Airflow, Redshift, Athena, Glue) Familiarity with data warehouses (Amazon Redshift, Google BigQuery, Snowflake) and testing data at scale Knowledge of data clean room technologies and testing secure data shares using RBAC Experience with version control systems (Git) and testing in CI/CD environments Understanding of workflow orchestration tools (Apache Airflow, Prefect, Dagster) for pipeline testing.