Full-Time Senior Data QA Engineer

Senior Data QA Engineer needed for Data Science team at Trella Health, focused on ensuring data accuracy and reliability for healthcare data. Leverage machine learning and other techniques to automate data QA, work with data scientists, engineers, and stakeholders to meet high data standards.

1. Develop, implement, maintain, and document a comprehensive data QA process and framework.
2. Continuously refine and optimize the data QA process, integrating new data sources.
3. Create new and maintain existing documentation for testing products.
4. Test data and solutions against business requirements to ensure alignment.
5. Validate data integrity, consistency, and accuracy across various data sources.
6. Conduct data validation, verification, profiling, and root cause analysis to identify quality issues.
7. Utilize machine learning techniques to automate the QA process.
8. Ensure high data quality standards, including healthcare claims data.
9. Proactively assess risks and identify issues early.
10. Stay informed of industry best practices and QA tools.
11. Guide team members on QA best practices.
12. Provide clear feedback to stakeholders on data quality issues.
13. Work with cross-functional teams to understand data requirements.
14. Participate in Agile/Scrum processes (planning, stand-ups, retrospectives).
15. Identify process improvements and contribute to data quality standards.

Qualifications:

• 5+ years experience in data quality assurance or data analysis.
• Experience with healthcare claims data.
• Proven experience with data validation, profiling, and root cause analysis.
• In-depth knowledge of data warehousing, ETL, and data pipelines.
• Ability to manage, analyze, and derive insights from large datasets.
• Experience with Python and SQL for data validation.
• Experience with machine learning for QA automation.
• Strong analytical and problem-solving skills.
• Excellent verbal and written communication skills.
• Bachelor's degree in Computer Science, Data Science, or related field.

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