## About Us 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, any where”. 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. ### Our Stack We build on a modern, production-grade foundation: Python, Django, PostgreSQL, and Redis on the backend, React and TypeScript on the frontend, and AWS, GCP, Docker, Kubernetes, and Temporal for infrastructure. Our AI/ML layer includes Claude and custom LLM integrations, agentic tooling, ambient scribing, and AI form-filling engines. We use Sentry for observability and GitHub with CI/CD pipelines and comprehensive testing frameworks for development. The Opportunity We're building the analytics platform that powers every operational workflow, customer-facing application, and AI product at Adaptive. Rather than treating analytics as a separate function, we embed governed business knowledge directly into software through semantic models, operational metrics, and agentic workflows. You'll help design the systems that define how humans and AI understand the business. A successful Data Engineer at Adaptive is analytical, detail-oriented, and comfortable working across the full stack, from raw ingestion to the semantic layers that power our applications and agents. 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 own the evolution of our analytics platform end to end, setting the technical vision for how business knowledge gets modeled, governed, and made reusable across engineering, operations, and product. This role is designed for you if you have a low ego, love solving problems that matter, and are ready to build an industry-changing company. What You'll Do 1. Own the analytics platform - Design and build the semantic models, metrics, and governance that power every operational workflow, internal application, and AI agent - Build domain abstractions that let engineers, operators, and AI reason about the business from a shared source of truth 2. Model complex healthcare domains - Model RCM workflows, clinical operations, and intake processes into scalable, well-governed systems that become a shared source of truth across the company - Design observability, feedback loops, and governance that keep the analytics platform trustworthy as we scale, from metric definitions to AI-generated decisions 3. Scale the platform alongside the product - Partner closely with product engineering to embed analytics directly into applications and agentic workflows - Contribute to the technical direction of the platform, scaling infrastructure to support growing operational needs and making it the foundation for AI-driven decision-making Must-Have Experience - 3+ years building and operating modern analytics platforms in a production environment - Strong SQL skills and experience designing data models, semantic layers, and metrics that enable reliable self-service analytics and AI applications - Experience with cloud data warehouses (Snowflake, Databricks, BigQuery, Redshift, or similar) and orchestration frameworks (dbt, Dagster, Airflow, or similar) - Proven ability to model complex business domains into scalable, well-governed systems that become a shared source of truth across engineering, operations, and product - Experience partnering closely with product and engineering teams to embed analytics into operational workflows, internal applications, or AI-powered systems - Strong systems design skills, with experience making architectural tradeoffs around data quality, governance, performance, and maintainability - Comfortable using Python (or similar) to automate workflows, build data tooling, or enable agentic processes ## What We Offer - Competitive salary and equity compensation - Comprehensive health insurance, dental, and commuter benefits - 401(k) retirement plan with employer contribution - 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 - Opportunity for growth in a fast-growing company - Collaborative team valuing innovation and problem-solving ## Location This role is in-person 3-5 days a week in our New York City office