Remote Healthcare Data Integration Engineer

Ursa Health, LLC; United States; On-site; USD 110,000 - 160,000; Full time

Job summary

Ursa Health, LLC is hiring a Data Integration Engineer to join our remote, US-based team. You will translate healthcare data into reusable data models and standards, building pipelines that connect claims, EMR, and billing data into the Ursa Core Data Model.

You’ll work with analytics engineering, product, and client teams to understand data needs, implement robust validation, and apply AI-assisted tooling to accelerate delivery while maintaining HIPAA compliance.

Qualifications

• 4+ years of experience with healthcare data integration (claims, billing, clinical).
• 4+ years building and maintaining ETL/ELT pipelines.
• Strong SQL and data modeling in relational databases.
• Excellent written and verbal communication skills.

Responsibilities

• Lead integration of complex healthcare data packages into data models.
• Design validation checks that preserve data integrity and analytics quality.
• Communicate with clients to understand data and intended analytical use cases.
• Document processes and final deliverables so non-technical stakeholders understand rules.
• Collaborate with analytics engineers, customer success, and product teams to align delivery with client needs.
• Support client teams with implementation, training, and measure interpretation.
• Thoughtfully leverage AI-assisted tooling to accelerate and improve delivery while ensuring sound output.
• Maintain HIPAA procedures and coordinate with Incident Response as directed.

Skills

SQL

Data Modeling

ETL/ELT pipelines

Healthcare data

Tools

Snowflake

dbt

Dagster

Airflow

Job description

Ursa Health, LLC is hiring a Data Integration Engineer to join our remote, US-based team. You will translate healthcare data into reusable data models and standards, building pipelines that connect claims, EMR, and billing data into the Ursa Core Data Model.

You’ll work with analytics engineering, product, and client teams to understand data needs, implement robust validation, and apply AI-assisted tooling to accelerate delivery while maintaining HIPAA compliance.