01Overview
Senior Quality Engineer Job Title: Senior Data Quality Engineer Experience: 68 Years Job Description: Own end-to-end data quality validation across ingestion, transformation, and consumption layers Design and maintain ETL automation frameworks using Python and Pytest Perform source-to-target validation, reconciliation, and anomaly detection Validate cloud-based data architectures (data lakes, warehouses, streaming platforms) Implement data quality rules such as null checks, schema validation, and integrity checks Use DataGaps (preferred) or similar tools for data quality monitoring Collaborate with data engineers, architects, and product teams to ensure quality Validate ETL workflows, scheduling, and failure handling mechanisms Execute SQL and Python-based validations for batch and real-time data Integrate automated data tests into CI/CD pipelines Track and report defects using Zephyr and Jira Ensure compliance with data governance and regulatory standards Mentor junior engineers and contribute to best practices and frameworks Required Skills: Strong experience in data pipeline validation, ETL testing, and data quality engineering Proficiency in Python, PySpark, SQL, and Pytest Experience with Selenium and DataGaps frameworks Knowledge of CI/CD tools (GitHub Actions) and version control (Git) Experience with AWS (Glue, Iceberg) and lakehouse architectures Familiarity with test data management techniques Experience with performance testing tools (JMeter) Experience with Zephyr test management tool Knowledge of Docker and Kubernetes Preferred: Experience with healthcare or regulated datasets Experience validating APIs, Tableau reports, and UI Familiarity with Agile methodologies Education: Bachelors degree in Computer Science, Engineering, or related field Experience Level Senior Level .
