Particle Health is looking to solve the problem of fragmented healthcare data by building an intelligent platform that focuses health back on the patient. They aim to enable healthcare innovators to access standardized, real-time patient data, bridging data silos to tackle use cases like care coordination, risk stratification, patient identity management, and regulatory compliance.
Requirements
- Strong skills in Python and SQL.
- Experience with Spark or other distributed data processing frameworks.
- Experience building or maintaining data pipelines, ideally using modern data tools (e.g., Airflow, Prefect, dbt).
- Experience working with healthcare data (such as EHR, FHIR, HL7, or claims data) — or a strong interest in learning healthcare data systems.
- Experience working with data lake or warehouse technologies (e.g., Iceberg, Delta Lake, BigQuery).
- Exposure to data modeling concepts and performance optimization.
- Familiarity with healthcare standards such as CCDA, FHIR, or HL7v2.
Responsibilities
- Build, maintain, and optimize scalable data pipelines for ingestion, transformation, and enrichment.
- Build sophisticated data and analytics products
- Support data quality, monitoring, and reliability across multiple healthcare datasets.
- Collaborate with product and engineering teams to design features that improve patient care.
- Help improve and evolve our data infrastructure to reduce manual work and improve efficiency.
- Partner closely with data scientists, product managers, and software engineers to understand data needs and deliver reliable solutions.
- Participate in code reviews, design discussions, and cross-functional projects.
Other
- 3+ years of experience in data engineering or a related role.
- Curiosity and problem-solving mindset — you enjoy exploring complex datasets and finding ways to improve them.
- Strong communication skills and comfort working with both technical and non-technical stakeholders.
- A proactive learner who enjoys tackling new challenges and growing in a fast-moving environment.
- Hybrid role based in New York City. The team works in-office two days per week (Tuesdays and Thursdays), so applicants should be within commuting distance and comfortable with in-person collaboration.
