Data Quality Engineer – Contract

This is a fully remote position, open to applicants in United States.

📋 Description

• Oversee data validation and reconciliation for extensive migrations involving medical claims, pharmacy claims, as well as eligibility and enrollment datasets.

• Confirm automated field mappings against legacy data warehouse definitions, identifying schema differences, value-domain mismatches, and transformation gaps.

• Collaborate with Data Engineering to facilitate issue resolution.

• Conduct comprehensive end-to-end ingestion testing on the new data ingestion platform.

• Reconcile outputs with legacy baselines, ensuring accuracy in record counts, field-level distributions, and business metrics against established quality thresholds.

• Design and implement SQL and Python-based data quality checks.

• Identify, document, and prioritize discrepancies, including missing records, value mismatches, schema drift, and downstream transformation errors.

• Establish and uphold data quality rules and validation thresholds for each data source.

• Document validation logic, sign-off criteria, and data caveats within migration tracking artifacts and run-book documentation.

• Aid in the transition from migration to steady-state operations by operationalizing data quality checks and monitoring.

• Contribute to ongoing data quality management efforts and mitigate recurring data issues.

• Work closely with the Head of Data Operations and interdisciplinary data, product, and platform teams.

⛳️ Requirements

• Bachelor’s degree with 3–5 years of experience in data quality engineering, data operations, or analytics (a Master’s degree may substitute for experience).

• Proven experience working with healthcare data, encompassing eligibility, enrollment, medical claims, and pharmacy claims.

• Advanced proficiency in SQL, including the ability to write complex queries and optimize them, as well as expertise in relational SQL database design, implementation, and optimization.

• Strong skills in Python and experience developing analytical or data validation workflows.

• Experience in data cleansing, curation, mining, manipulation, and analysis from various systems.

• Demonstrated experience in supporting large-scale data migrations, specifically in source-to-target validation and data reconciliation.

• Experience validating data pipelines and ETL transformation logic, including field mappings, derived fields, and aggregated business metrics.

• Ability to analyze complex, imperfect datasets, identify root causes, and resolve data-related issues.

• Experience in owning or contributing to data quality processes, including defining validation logic and maintaining data integrity.

• Strong collaboration skills when working with data engineering, product, or analytics teams.

• Capability to complete a practical SQL and Python-based exercise using representative healthcare data.

🏝️ Benefits

• Play a critical role in transforming healthcare benefits and data management.

• Opportunity to shape and develop a high-quality, passionate team.

• Work with cutting-edge technologies in cloud computing, data engineering, and healthcare data processing.

• Initial contract term of up to one year.