Senior Software Engineer - Data [NYC or SF]

About Amigo At Amigo, we're building the clinical AI infrastructure that health systems, life sciences companies, payors, and government agencies run their patient-facing care on. Our agents work across the whole patient journey: pre-visit intake, care navigation, post-visit care plans, and ongoing monitoring. Our mission is to make excellent care accessible to every patient, not rationed by the limits of clinician time. This hasn’t been solved because the underlying record was never built for it. EHRs were designed for billing, not for systems that learn. So instead of layering another point solution on top, we’re rebuilding the medical record as a timeline of clinical events and running agents on top of it that improve with every patient interaction. Unlike single-purpose chatbots or scribes, Amigo is the platform our customers use to build their own agents. That means our work has to hold up across specialties, workflows, and regulatory environments and not just one narrow use case. Our agents have supported more than 4 million patient encounters and are on track to grow tenfold this year. Our work is validated through partnerships with leading academic medical institutions. We’re fresh off our Series A, backed by Tier 1 VCs such as Madrona, General Catalyst, and Optum Ventures. We’re a small team of around 35 people, working in person in New York City and San Francisco. [... source excerpt omitted ...] good ideas reach patients. If you want your work to be measured in outcomes rather than releases, we’d like to hear from you. About this role As a Senior Data Engineer at Amigo, you'll build the data layer everything else runs on. Healthcare organizations already keep their data in EHRs, schedulers, and warehouses. Your job is to pull that data in, keep it current, and turn scattered records into one accurate picture of each patient and provider. If the data is wrong or stale, everything above it breaks, so correctness is the work, not a nice-to-have. You'll own it end to end: ingestion, transformation, modeling, and the query tools teams use. What you'll do Building integr [... source excerpt omitted ...] Powering natural language query interfaces over healthcare data Owning data modeling, query performance, and data freshness at scale What we're looking for Built and operated production data platforms that ingest, process, and serve millions of events with high reliability Designed scalable streaming and batch pipelines, data models, and ETL/ELT workflows for production systems Possess deep expertise in SQL, distributed query optimization, and large-scale data processing Have hands-on experience with modern data platforms such as Databricks, Snowflake, Delta Lake, Apache Iceberg, Spark, Kafka, or similar technologies Designed event-driven architectures, change data capture