Software Engineer [Data Ingestion + Customer Integration]

Phare Health is on a mission to fundamentally reimagine healthcare payments by making reimbursement transparent and fair (/phare). We specifically focus on the most complex AI challenges that require novel R&D, with a team that blends AI researchers and engineers with clinicians, and payment experts.Founded by former leaders from DeepMind and Google Health and backed by General Catalyst, we’re scaling quickly - join us!

Phare's delivery team is looking for a Software Engineer to own data ingestion to implement Phare’s platform at partner provider and payer systems. You’ll work closely with customer IT teams to integrate Phare via HL7, X12, SFTP, and API pipelines, resolving data fidelity issues along the way.

This is a hands-on role at the intersection of healthcare data, systems integration, and architecture. You’ll bridge our cutting-edge AI product with real-world health data infrastructure to ensure we can deliver a smooth, reliable experience for our customers.

What You’ll Do

• Use Python and other object-oriented programming languages extensively

• Participate in the core team leading end-to-end integration with provider and payer IT teams, from requirements gathering to go-live

• Design and implement data pipelines (HL7, X12, SFTP, APIs) to connect EHR, claims, and payer systems into Phare

• Set up validation & quality checks for integrity and accuracy of ingested data

• Monitor data pipelines and services to ensure data is available reliably

• Resolve data fidelity, transformation, and mapping challenges to ensure accurate, usable inputs for Phare’s models

• Collaborate with Phare’s engineering, product, and data science teams to align technical integration and product requirements, improve data processing efficiency, reduce latency, and enhance overall system performance

• Troubleshoot issues effectively across internal and external stakeholders

• Document integration architectures and contribute to building repeatable, scalable integration playbooks

• Ensure compliance with healthcare security and privacy standards, including HIPAA and data governance best practices
  

• Problem Solver: Able to debug messy healthcare data and build solutions that are robust, scalable, and compliant

• Systems Thinker: Experience architecting or scaling integrations that balance reliability, performance, and security

• Collaborator: Skilled at working with customer IT teams, clinical/operations stakeholders, and internal product/engineering peers

• Startup Mindset: Comfortable in a fast-moving environment, eager to take ownership and shape integration processes as we scale
  

Bonus Points

• Experience with cloud-based integration platforms (AWS/GCP, Mirth, Redox, etc.)

• Familiarity with cloud-based data workflows and scheduling/orchestration frameworks (e.g. Apache Airflow) is a plus

• Familiarity with healthcare claims data and reimbursement workflows (e.g., in EHRs, claims, payer systems, or healthcare APIs)

• Hands-on experience with HL7, X12, FHIR, SFTP pipelines, and healthcare interoperability standards

• Exposure to data validation, analytics, or ML-driven use cases
  

• Work side-by-side with world-class founders from DeepMind, Google Health, and Stanford

• Help build a category-defining company tackling one of the most broken parts of healthcare

• Grow into a leadership role as Phare scales, with potential to shape integration strategy and lead a growing team.
  

Benefits

• Competitive salary (top-of-market depending on seniority, $150-220k) + equity

• 401(k) with company match

• ICHRA health insurance plan tailored to your needs

• Flexible PTO + bonus birthday day off

• Hybrid New York HQ, with remote flexibility and “work from anywhere” up to 1-month/year

• Collaborative team culture with 3-days/week at SoHo HQ (fully-remote considered on exception), regular outings, and twice-a-year offsite events

Hiring Process

1. Initial application

2. Intro call – discuss your background, career goals, and our mission

3. 2 x Technical interviews – coding for real-world data challenges, and systems design

4. References – we ask for two

5. Culture interview – ways of working and chance to ask questions

6. Offer