Data Engineer
CORMAC
Data Engineer - Healthcare IT CORMAC is seeking a Data Engineer to design, build, and operate the data integration and processing pipelines for the CMS Reporting and Quality division. This role works hands-on in Databricks and AWS with Medicare claims data, patient assessment data, and provider demographic sources to produce validated claims-based and hybrid quality measure outputs for confidential provider reports and public reporting. Responsibilities:
- Design, build, and maintain scalable data pipelines in Databricks (Spark with Scala and/or PySpark, and SQL) that ingest, integrate, validate, and transform Medicare claims, patient assessment, and provider demographic data
- Develop, schedule, and optimize Databricks jobs, notebooks, and workflows, and tune Spark performance and cluster cost for large-scale claims processing
- Process Medicare claims and encounter data, including claim types, variables, values, and final action record logic
- Implement claims-based and hybrid quality measure specifications, including risk adjustment and imputation, using Databricks, SQL, PL/pgSQL, PostgreSQL, Python, SAS, and R as appropriate
- Build and integrate pipelines with AWS services such as S3, Glue, Lambda, SQS, EventBridge, EMR, Redshift and Redshift Spectrum, and RDS for PostgreSQL
- Produce confidential provider-level quality measure feedback reports and public reporting files on weekly, monthly, and quarterly cycles
- Apply matching rules across provider identifiers such as internal system provider IDs, CCNs, and NPIs, and geographic indicators, to track provider demographic changes such as address, certification, and ownership changes
- Implement patient and resident ID assignment, assessment matching, episode and stay building, and de-duplication routines
- Implement automated data validation frameworks, ETL/ELT testing suites, and statistical anomaly detection to validate measure logic, stored procedures, and output schemas before release
- Support relational schema and virtual data mart design for multi-dimensional, longitudinal analysis, and ensure de-identification and data security requirements are met for PII and PHI
- Prepare data pipelines for HL7/FHIR and digital quality measure data standards by applying the same core ingestion and validation logic
- Bachelor's degree in Computer Science, Information Technology, Statistics, Data Science, or a similar field
- Must be a U.S. Citizen
- Must be able to obtain a Public Trust (Tier I) Clearance
- Minimum of 7+ years of experience in data engineering, ETL/ELT development, or database development
- Minimum of 3+ years of hands-on experience building and operating production data pipelines in Databricks using Spark (Scala and/or PySpark) and SQL
- Advanced SQL skills and strong experience with PostgreSQL or another enterprise relational database, including stored procedures
- Hands-on experience with AWS data services such as S3, Glue, Lambda, and Redshift or RDS
- Experience validating data and outputs, including automated testing of ETL/ELT pipelines and data quality checks
- Experience working with large-scale healthcare data and protecting sensitive PII and PHI in accordance with HIPAA
- Strong communication skills with the ability to work in a cross-functional Agile team
- Master's degree in a relevant field
- Databricks certification (for example Databricks Certified Data Engineer Associate or Professional)
- Experience with Medicare and Medicaid claims data and CMS data assets
- Experience with CMS quality measure calculation, risk adjustment, and CMS quality reporting programs
- Experience with SAS and R, and with Snowflake
- Experience with provider data sources and provider identifier resolution (CCN, NPI)
- Experience with Amazon EMR and Redshift Spectrum
- Experience with HL7/FHIR data standards
- Experience producing public reporting files
Vacancy posted 3 days ago
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