Phare is building healthcare's first Revenue Operating System that uses AI to make hospital billing and reimbursement effortless, accurate, and fair. The company is looking to solve the problem of complex and inefficient healthcare payment systems.
Requirements
- Experienced in architecting and building microservices and ETL pipelines in Python, Go, or Java.
- Experienced building and managing infrastructure with Terraform, Docker, and Kubernetes.
- Strong with Spark, Airflow, or Kafka for orchestrating and streaming data flows; comfortable managing dependencies, scheduling, and state in complex workflows.
- Adept at implementing observability and reliability practices, instrumenting pipelines with logs and metrics to detect drift, latency, and data quality issues before they impact users.
- Experience with the data backend behind a production-grade ML system and/or a user-facing SaaS application.
- Experience with high-throughput data pipelines.
- Experience with healthcare data (FHIR, HL7) - Bonus
Responsibilities
- Own the data foundations of the Phare stack - the backend schemas and APIs that power both the AI engine and the user-facing application.
- Work on reliable systems for ingesting, transforming, and serving large-scale healthcare data.
- Ensuring high performance, observability, and security/compliance for data systems.
- Architecting and building microservices and ETL pipelines.
- Building and managing infrastructure with Terraform, Docker, and Kubernetes.
- Orchestrating and streaming data flows using Spark, Airflow, or Kafka.
- Implementing observability and reliability practices, instrumenting pipelines with logs and metrics.
Other
- This is an in-person role in NYC requiring at least 3 days in the SoHo office.
- 5 years of software engineering experience
- Intro call - your background & our mission alignment
- Culture interview in person in NYC
- References
