Data Integration Engineer

Role Overview

• Lead the integration of complex healthcare data packages including medical claims, pharmacy claims, revenue cycle billing, ADT, clinical/EMR, FHIR and value-based care financial datasets into custom or Ursa Studio standard data models through collaboration with client and Ursa Health teams.
• Design and operationalize rigorous validation checks that preserve data integrity, prevent analytics degradation, and maintain client trust.
• Communicate with clients to understand their data, its limitations, and intended analytical use cases to support them in interpreting the findings that drive their businesses.
• Effectively communicate with internal and client teams to gather and understand the information necessary to successfully complete projects, documenting both the process and final deliverables so a non-technical stakeholder can understand the interpretation and business rules.
• Collaborate with analytics engineers, customer success, and product teams to align delivery with client expectations and to surface product opportunities informed by client needs and data behavior.
• Support client teams to advance their implementation initiatives, including training, measure building, and report interpretation.
• Thoughtfully leverage AI-assisted tooling to accelerate and improve delivery, applying domain knowledge and human judgment to ensure sound output.
• Keep your knowledge current regarding data security and privacy procedures and policies.
• Comply with HIPAA procedures and collaborate with the Incident Response Team as directed.

Requirements

• 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.

Tech Stack

• ETL
• Oracle
• Postgres
• SQL

Benefits

• Flexible work arrangements
• Remote work options
• Inclusive environment