Data Quality Engineer
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Job Summary
To ensure the accuracy and reliability of enterprise data platforms, the hybrid Data Quality Engineer will design and automate data quality testing frameworks using dbt and Python, while integrating quality controls into CI/CD pipelines through Azure DevOps.
Key responsibilities
- Design, build, and maintain automated data quality tests in dbt, including schema tests and source freshness checks
- Develop Python-based validation frameworks for data reconciliation and regression testing, validating data pipelines in Databricks
- Define and monitor data quality metrics, triage data defects, and contribute to data governance and quality standards
Required qualifications
- 5+ years in QA, data testing, or data engineering roles focused on data validation
- Hands-on experience with dbt, including tests, macros, and models
- Strong Python skills for test automation, including experience with pandas and PySpark
- Practical experience with Databricks and Azure Pipelines for CI/CD
- Solid understanding of data quality concepts and frameworks
Complete Job Description
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