AI-powered automation for healthcare revenue operations, streamlining denied and unpaid claims
Data Engineer
You'll spend mornings untangling EDI 835 files that providers have wrestled with for decades, building Airflow pipelines that turn messy claim statuses into clean, queryable datasets by lunch. Afternoons go toward modeling the denial patterns that cost hospitals millions—reason codes, payer quirks, timing anomalies—so downstream systems can predict and prevent them. The work sits at the intersection of healthcare finance and machine learning: reliable data infrastructure first, intelligent automation second.
What they're looking for
- 3+ years building production data pipelines, with deep Python fluency and hands-on Airflow experience
- Demonstrated work with healthcare data formats (HL7, X12/EDI, FHIR) or complex financial/claims datasets
- Strong SQL and data modeling skills; you design schemas that account for edge cases and evolving specs
- Comfort shipping independently in a small team—clear documentation and ruthless prioritization matter more than process theater
- Familiarity with cloud-native data stacks and cost-conscious engineering; you've felt the sting of an unexpected BigQuery bill