Python Data Test Automation (RARR Job 5848)

We are seeking a detail-oriented Data Quality Engineer with strong expertise in SQL, Python, and modern data platforms. The ideal candidate will have experience validating large datasets, ensuring data integrity, and building automated testing frameworks. This role also involves leveraging tools like Selenium for end-to-end testing and ensuring the reliability of both data pipelines and applications.

Primary Responsibilities

• Design and implement data quality checks and validation frameworks for large-scale datasets.

• Develop automated test scripts using Python, SQL, and Selenium to validate data pipelines and application workflows.

• Collaborate with data engineers, analysts, and QA teams to ensure high-quality data delivery.

• Work with modern data platforms such as Snowflake, Databricks, Spark, and Airflow to build and monitor data pipelines.

• Perform root cause analysis and resolve data quality issues in production systems.

• Document test cases, validation rules, and quality metrics to support continuous improvement.

Good to Have (Preferred Skills)

• Experience with BDD frameworks (e.g., Behave, Cucumber) for automated scenario development.

• Hands-on experience in AWS or other cloud environments for scalable data solutions.

• Familiarity with open-source data quality tools such as Deequ, Great Expectations, or custom frameworks.

• Knowledge of CI/CD practices and integration of Selenium tests into pipelines.

• Strong understanding of data governance, lineage, and compliance requirements.