Data Engineer

Revolutionizing Us Healthcare

We are fixing US healthcare by building an AI-native physical care platform, starting with home health. Home health is a $140B industry with less than $10B in EBITDA — 40% of revenue is spent on pure administrative waste. We automate this work with AI, creating a fundamentally different cost structure compared to incumbents. This lets us rapidly take market share by serving the 30% of patients who go untreated today. By reshaping the cost structure of this industry, we unlock its growth.

We've built one of the best AI teams in the world (from Character AI, Scale, Palantir, Citadel, Jane Street) and paired them with a team of healthcare veterans and ex-MBB strategists to build a new type of healthcare company: one that delivers care at the speed of an AI company. Our physical care platform already operates with 30pp higher gross margins than traditional home health providers. With our AI advantage, we pay nurses more, remove their admin burden, and unlock the scale economics that have been missing from this fragmented industry. If we served this entire $140B market, instead of $10B in EBITDA, we'd drive $60B. We're starting with home health, then expanding to all delivered care. Our mission is "any care, anywhere". Fundamentally, our incentives are aligned with America. Every dollar in revenue we make is two dollars taken out of the healthcare system. If we succeed, so does US healthcare.

About the Role

We're hiring a Data Engineer to build the data infrastructure that powers business intelligence, operational analytics, and AI-driven decision-making across our platform. You'll design and implement data pipelines, integrate disparate healthcare data sources, and model complex domains like RCM, intake, and clinical operations to enable real-time insights and automation. A successful Data Engineer is analytical, detail-oriented, and comfortable working across the full data stack—from raw ingestion to analytics-ready models. You'll have significant ownership over our data architecture and the opportunity to define how we measure, monitor, and optimize every aspect of our operations. Over time, you'll take end-to-end ownership of our data platform, setting the technical vision for data infrastructure and enabling data-driven insights that shape product and business decisions.

Responsibilities

• Design, build, and maintain robust data pipelines that integrate data from multiple sources including EMRs, EDI feeds, internal systems, and third-party APIs.
• Develop and manage data infrastructure using modern data stack technologies (Postgres, Databricks, Redshift, or similar warehouses).
• Model complex healthcare domains (RCM workflows, clinical operations, intake processes) into clean, queryable data schemas that support analytics and reporting.
• Build analytics, alerting, and dashboards to identify and prioritize opportunities for automation or process improvement across the business.
• Contribute to the technical direction of our Business Intelligence platform, scaling data infrastructure to support growing operational needs.

Qualifications

• Data Engineering Experience: 3+ years building and maintaining data pipelines, warehouses, and analytics infrastructure in a production environment.
• Technical Proficiency: Strong experience with SQL and at least one modern data warehouse (Databricks, Redshift, Snowflake, BigQuery) and relational databases (Postgres, MySQL).
• Analytics & Data Science: Comfortable with statistical analysis, exploratory data analysis, and applying analytical techniques to solve business problems. Familiarity with Python or R for data analysis.
• Pipeline Development: Experience building ETL/ELT pipelines using modern orchestration tools (Airflow, dbt, Dagster, or similar).
• Collaboration & Communication: Ability to translate technical data concepts for non-technical stakeholders and partner effectively with Product and Engineering teams.

Preferred:

• Experience in healthcare technology, especially with healthcare data standards (EDI, HL7, FHIR, claims data, clinical documentation).
• Experience with real-time or streaming data pipelines.
• Background in data science or machine learning, including feature engineering for AI/ML systems.
• Exposure to business intelligence tools (Hex, SigmaComputing, or similar).

What We Offer

• Opportunity for growth in a fast-growing company
• Collaborative team valuing innovation and problem-solving
• Competitive salary and equity compensation
• Flexible time off policy—we expect most employees to take at least 3 weeks of vacation per year
• In-office lunches, dinners, and snacks to fuel your focus and well-being
• 401(k) retirement plan with employer contribution
• Comprehensive health insurance, dental, and commuter benefits

Location

This role is in-person 3 days a week in our New York City office