Data Quality Engineer

📋 Description

• Lead data validation and reconciliation activities for large-scale migration initiatives involving
• Validate automated field mappings against legacy warehouse definitions, identifying schema
• Partner with Data Engineering and other technical teams to investigate discrepancies and drive
• Perform end-to-end ingestion testing by executing test files, comparing results with legacy
• Design and maintain SQL- and Python-based data quality checks, including source-to-target
• Identify, document, and triage missing records, value mismatches, schema drift, transformation

🎯 Requirements

• Bachelor’s degree with 3–5 years of experience in data quality engineering, data operations
• Direct experience working with healthcare datasets, particularly eligibility, enrollment, medical
• Advanced SQL expertise, including developing, optimizing, and implementing complex queries within
• Strong Python programming skills with experience developing analytical and data-validation
• Experience cleansing, curating, mining, manipulating, and analyzing data from disparate systems.
• Demonstrated experience supporting large-scale data migrations, including source-to-target

🎁 Benefits

• Estimated compensation of $40–$60 per hour.
• Remote contract opportunity available to professionals located in the United States.
• Initial contract term of up to one year.
• Opportunity to contribute to a large-scale healthcare data migration with direct impact on data
• Exposure to modern cloud computing, data engineering, and healthcare data-processing technologies.
• Close collaboration with data operations, engineering, product, and analytics professionals.