EHR Interoperability Lead

Chamber Cardio • Washington, DC

3d • Remote

About The Position

Chamber Cardio is building the connective tissue between our value-based cardiology network and the practices we serve. We’re hiring an EHR Interoperability Lead to own how clinical data moves in and out of local practice EHRs — making sure the right notifications, care gaps, and transitions-of-care signals reach providers inside the tools they already use.
This is a hands-on, build-it role. You’re equally comfortable wrangling an HL7 feed, reasoning about FHIR resources, and finding a pragmatic workaround when a practice’s system won’t cooperate. You don’t need to be a software engineer — but you do need to know EHRs from the inside, move data confidently on your own, and use AI to do the work of three people.

Requirements

• 5-7+ years of experience in healthcare technology, EHR implementation, or interoperability
• Deep, hands-on experience with healthcare interoperability standards: FHIR, HL7v2, and C-CDA
• A track record integrating with multiple EHR systems at the practice or health-system level
• Comfort operating across the spectrum from clean API integrations to scrappy, get-it-working approaches
• Fluency with clinical and value-based care concepts: eligibility, claims, attribution, transitions of care, and GDMT
• AI-native and genuinely curious about automation. You can automate yourself into being 3x as effective using SQL, Python, or tools like Claude — and you’ll pass a basic coding assessment
• A pragmatic, ownership-minded approach — you simplify what’s overcomplicated, and you ship

Responsibilities

• Own read/write integrations with practice-level EHRs across our network, using standards-based interfaces (FHIR, HL7v2, C-CDA) and pragmatic, get-it-working methods where the standards fall short.
• Design and ship clinical notifications to practices — GDMT prompts, care gaps, ADT-triggered discharge alerts, and transitions-of-care signals — so they land inside provider workflows, not a separate portal.
• Apply AI tooling to extract, normalize, and route unstructured clinical data where direct integration isn’t possible.
• Support partner and payer data integrations — ingesting eligibility files, claims, and attribution data, and producing return files, in step with our analytics stack (dbt, attribution logic).
• Partner across teams — clinical, network, and practice-facing — to translate operational needs into reliable data flows.
• Build for durability: the monitoring, error-handling, and documentation that keep these integrations dependable as we scale.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Education Level: No Education Listed