Data Engineer
Cormac Corporation Leesburg, Virginia, United States · $115K–$190K/yr
IT Services and IT Consulting · 51-200 employees
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About the role
Design, build, and maintain scalable data pipelines in Databricks to process Medicare claims and provider demographic data. Ensure data quality through automated validation frameworks and produce validated quality measure reports for public and confidential use.
What they look for
Requirements
Requires a Bachelor's degree and at least 7 years of experience in data engineering or database development. Candidates must be U.S. citizens capable of obtaining a Public Trust (Tier I) clearance and possess hands-on experience with Databricks, AWS, and healthcare data security.
Benefits
Full description
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
Basic Qualifications:
- 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
Preferred Qualifications:
- 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
Why CORMAC?
At CORMAC, we leverage the power of Data Management and Analytics to enable our customers to achieve their strategic goals. With over 20 years of experience in Health Information Technology (HIT), human-centered design principles and Agile development methodologies, CORMAC delivers complex digital solutions to solve some of the most challenging problems facing public healthcare programs today.
As a US Federal Government contractor in the public healthcare sector, our work is impactful and cutting-edge while being performed in a supportive, collaborative, and welcoming environment. We offer flexible work schedules with remote, hybrid, or fully in-person workplace options to empower our employees to decide the workplace most suitable for them. At CORMAC, we have a highly diverse workforce, and believe the work environment is a place where creativity, collaboration, enthusiasm, and innovation happens, regardless of location.
E-Verify Participation/EEO
As an Equal Employment Opportunity employer, CORMAC provides equal employment opportunity to all employees and applicants without regard to an individual's protected status, including race/ethnicity, color, national origin, ancestry, religion, creed, age, gender, gender identity/expression, sexual orientation, marital status, parental status, including pregnancy, childbirth, or related conditions, disability, military service, veteran status, genetic information, or any other protected status.
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