Assist in building and maintaining ETL/ELT pipelines for healthcare datasets including claims, eligibility, provider, risk adjustment, HEDIS, EHR, and clinical data
Support the development of data models and data transformations aligned with healthcare standards (e.g., HL7, FHIR, X12)
Contribute to data quality checks, validation rules, and documentation for healthcare data assets
Work with analysts and business users to understand data requirements and translate them into technical tasks
Assist in ingestion and integration of new data sources from EMR systems, CMS feeds, and vendor partners
Develop SQL queries, transformations, functions, and stored procedures to support reporting and analytics workflows
Support data platform tools such as Azure Data Factory, Databricks, Python/Spark jobs, and version control workflows
Participate in issue resolution related to data pipeline failures or data quality errors
Maintain data dictionaries, mapping files, and documentation as part of data governance processes
Collaborate with senior engineers to implement best practices in security, compliance (HIPAA), and architecture

2–4 years of experience in data engineering, ETL development, or data integration (healthcare experience preferred)
Strong SQL skills and experience working with relational databases
Basic to intermediate experience with Azure Data Factory, Databricks, PySpark, or comparable ETL tools
Familiarity with healthcare data types such as claims, eligibility, provider files, or EHR data
Knowledge of interoperability formats (HL7, X12, FHIR) is a strong plus
Basic Python or Scala programming skills
Understanding of data warehousing concepts and modern data architectures
Ability to learn quickly and work collaboratively with technical and non-technical teams
Strong communication, documentation, and organizational skills
Bachelor’s degree in Computer Science, Information Systems, Healthcare Informatics, or related field (or equivalent experience)

Data Engineer

Key skills