Job Description

Founding Senior Backend Engineer (Data Platform / Integrations)

Location: New York City — In-Person

The Opportunity

Our client is hiring a Founding Senior Backend Engineer to own the data platform end-to-end and build the team around it. This is a true founding role: you will define canonical data models, ship the event backbone, enable analytics/experimentation, and create the integration architecture that makes adding EMR #5 configuration—not months of bespoke engineering.

If you’re energized by unglamorous but high-leverage infrastructure (data modeling, pipelines, events, integrations), this is a rare seat.

What You’ll Own

1) Outcome Data Layer (Instrumentation + Measurement)

Build the instrumentation layer that ties every agent decision to customer-level business metrics—e.g., client retention, caregiver satisfaction, authorization utilization, hours erosion. This becomes the foundation for experimentation, ROI claims, ML improvements, and product strategy.

2) Real-Time Event Backbone

Design an event-driven architecture where visit status changes, clock-ins, call-outs, ranking decisions, and workflow outcomes flow in real time—so internal systems (and future products) can consume events without constant EMR polling or rate-limit band-aids.

3) Integration Platform + Canonical Models

Create canonical data models across WellSky, HHAeXchange, AlayaCare, and Axxess so adding the next EMR is configuration-driven. This also unlocks revenue-cycle automation by enabling unified authorization and billing models.

4) Analytics & Experimentation Tooling

Build the warehouse + tooling so engineers can answer: “Did this change improve customer outcomes?” quickly and consistently—without writing one-off queries every time.

What Our Client Is Looking For

You’re likely a fit if you are:

• Systems-minded and data-opinionated: you treat data modeling as a craft and can explain why entities should relate a certain way
• Comfortable with messy reality: you’re excited by pipelines, joins, ETL/ELT, and cleaning inconsistent third-party data
• Event-driven by default: you’ve built (or deeply understand) real-time architectures, streaming/event backbones, and durable systems
• Integration-savvy: you’ve shipped platforms that unify multiple external systems into clean internal abstractions
• AI-native and curious: you naturally look for leverage (LLMs for parsing/structuring, automation for data QA, agent-based extraction when APIs don’t exist)

Bonus signals

• Experience with healthcare workflows, EMRs/EHRs, home health, or revenue-cycle concepts (authorization, billing, reimbursement)
• Familiarity with healthcare data modeling standards (e.g., FHIR-style entity thinking)
• Experience building experimentation frameworks or measurement systems tied to business outcomes
• Background in data platform teams (data engineering + backend/platform) at high-growth startups

What Success Looks Like (The Arc)

Q2: Ship the outcome data layer + real-time event backbone. Make experimentation and measurable ROI a default.
Q3: Deliver the integration abstraction + canonical models. EMR #5 becomes configuration. RCM roadmap becomes real.
Year-end: You’ve built and are leading a 3–5 person data platform team (integration, data engineering, analytics). You’re operating as the Head of Data Platform.

Why This Role

• Founding-level ownership on a platform that directly drives revenue outcomes
• Complex, high-impact systems work: data, events, integrations, measurement, experimentation
• Clear path to technical leadership and building a team
• Real customers, real workflows, and real-world leverage—your architecture decisions compound fast