Data Engineer
NDAPARTNERS INC.
United States
24 days ago
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Role details
Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
5 years minimum
Working hours
Regular working hours
Job source
Tech stack
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
+4 more
Data Streaming
Snowflake
Data Lineage
Amazon Redshift
Job 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
Requirements
- 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
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