Data Integration Engineer

Role Description

The Data Integration Engineer role is ideal for an experienced data professional eager to put their healthcare domain knowledge and engineering expertise to work in a collaborative, mission-driven environment. Your efforts to organize, transform, and automate the flow of healthcare data will unlock actionable insights for our clients, enabling them to move from raw data to meaningful analysis in hours rather than weeks.

• Interpret and integrate client data claims, ADT, clinical/EMR, provider billing, and other operational datasets into the Ursa Core Data Model.
• Build reusable, enduring data models that clients rely on to drive clinical, operational, and financial decisions.
• Work closely with Ursa colleagues across analytics engineering, product development, and customer success.
• Collaborate directly with client teams including data architects, analysts, clinicians, and other healthcare professionals to understand their data and needs.
• Leverage Ursa Health's data platform to design and build integration pipelines and data models.
• Work alongside AI-assisted tooling that accelerates the process.

Qualifications

• Bachelor’s degree
• 4+ years of experience working with healthcare financial (e.g., claims, provider billing data), clinical or pharmacy data domains
• Familiarity with healthcare data integration concepts, common data sources (payer data files, EMR/EHR systems), data formats (claims, billing, X12 835/837/270, HL7 ADT, FHIR), and medical coding standards (CPT, ICD-10)
• 4+ years implementing and maintaining ETL/ELT pipelines and processes.
• 4+ years of experience in end-to-end data integration (data discovery, data cleansing and curation, analysis, transformation, validation and maintenance).
• High proficiency working with SQL, relational database systems (e.g., Snowflake, Microsoft SQL, Oracle, PostgreSQL) and data modeling.
• Excellent written and verbal communication skills.

Requirements

• Knowledgeable in healthcare interoperability / integration engines
• Experience with ELT or workflow orchestration tools such as Fivetran, dbt, Dagster, or Airflow.
• Experience building data models that support healthcare outcome measurement.
• Familiarity with value-based care data and financial models.
• Working understanding of Python or JavaScript to manipulate and transform large datasets and data science fundamentals.
• Experience working with AI tools in a professional context, with the judgment to apply them appropriately in healthcare data environments where output accuracy is critical.
• History of working with remote teams.

Benefits

• Remote position
• Collaborative team environment
• Opportunity to work with cutting-edge technologies