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# Data Engineer

- **Company:** NDAPARTNERS INC.
- **Location:** United States (Remote available)
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Java (Programming Language), Airflow, Automation of Tests, BigQuery, Information Engineering, Data Integrity, Extract Transform Load (ETL), Data Warehousing, Database Queries, Healthcare Effectiveness Data and Information Set, Python (Programming Language), Operational Databases, Data Streaming, Snowflake, Data Lineage, Amazon Redshift
- **Published:** September 14, 2026
- **Apply:** https://www.dice.com/job-detail/24d6f6d2-1b78-440d-92f8-8812ef258ee8

## About the Role

* 5+ years of experience in data engineering or a closely related field, including direct HEDIS experience
 * Hands-on experience with HEDIS measure specifications (NCQA Volume 2) and HEDIS reporting cycles
 * Familiarity with healthcare data types relevant to HEDIS: claims, encounters, eligibility, pharmacy, lab, and supplemental data
 * Strong SQL skills and hands-on experience with at least one major data warehouse (Snowflake, BigQuery, Redshift, or similar)
 * Proficiency in Python or Scala/Java for building production data pipelines
 * Experience with modern orchestration tools (Airflow, Dagster, Prefect, or similar)
 * Solid understanding of data modeling, dimensional design, and ETL/ELT best practices in a healthcare context
 * Experience working with or alongside HEDIS/quality measure engines (e.g., Inovalon, Cotiviti, MedInsight, or custom rules engines) is a plus

## Description

* Design, build, and maintain scalable batch and streaming data pipelines supporting HEDIS measure calculation and reporting
 * Ingest and transform claims, encounter, lab, pharmacy, and supplemental data feeds used in HEDIS measure logic
 * Implement and maintain HEDIS measure specifications (NCQA Volume 2) in code, ensuring accurate translation of clinical logic into data transformations
 * Support annual HEDIS reporting cycles, including hybrid measure data collection, rate calculation, and submission-ready extracts
 * Build automated testing and validation to confirm HEDIS measure outputs match specification and prior-year trends
 * Partner with quality/clinical teams, compliance, and analytics to understand measure requirements and NCQA/CMS updates each year
 * Investigate and resolve discrepancies in HEDIS rates, source data gaps, and measure logic issues
 * Maintain clear documentation of data lineage, transformation logic, and measure mappings for audit and NCQA review purposes
 * Continuously improve pipeline architecture for scalability, performance, and data integrity across HEDIS reporting workflows