Senior Quality Engineer

Job Title: Senior Data Quality Engineer Experience: 6–8 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: • Bachelor’s degree in Computer Science, Engineering, or related field