Thesis is building an AI-powered care team platform to increase clinical capacity. We are based in New York City and backed by $60 million in funding from Oak HC/FT, CRV, Black Opal Ventures, and experienced healthtech investors. About the role: We are seeking a highly driven Data Engineer to design, build, and scale the data foundations powering Thesis’s AI agents, including owning critical client integrations. You will partner with product, engineering, and AI/ML teams to ensure the data architecture is scalable, reliable, secure, and actionable. This is a broad-scope, high-impact role for a technical builder who thrives in ambiguity and wants ownership over modern data infrastructure in an early-stage healthcare startup. Responsibilities: Design and build core data infrastructure; implement and maintain scalable data pipelines across ingestion, transformation, and storage; own client integrations and ETL workflows; design robust data models; enable product and analytics outcomes; drive data quality and observability. Requirements: 4–6+ years of experience in Data Engineering or Software Engineering with a data focus; strong Python and SQL; hands-on experience with cloud data platforms (AWS and/or GCP), data warehouses (Snowflake, Redshift, or BigQuery), orchestration tools (Airflow or similar), and transformation tools (dbt preferred); healthcare data experience (FHIR/HL7, EHR APIs); data modeling expertise; clear communication. NYC-based: based in New York and in-office 3+ days per week. Compensation target: $170-$250k, plus equity and a generous benefits package. Thesi

Thesis is building an AI-powered care team platform to increase clinical capacity. We are based in New York City and backed by $60 million in funding from Oak HC/FT, CRV, Black Opal Ventures, and experienced healthtech investors. About the role: We are seeking a highly driven Data Engineer to design, build, and scale the data foundations powering Thesis’s AI agents, including owning critical client integrations. You will partner with product, engineering, and AI/ML teams to ensure the data architecture is scalable, reliable, secure, and actionable. This is a broad-scope, high-impact role for a technical builder who thrives in ambiguity and wants ownership over modern data infrastructure in an early-stage healthcare startup. Responsibilities: Design and build core data infrastructure; implement and maintain scalable data pipelines across ingestion, transformation, and storage; own client integrations and ETL workflows; design robust data models; enable product and analytics outcomes; drive data quality and observability. Requirements: 4–6+ years of experience in Data Engineering or Software Engineering with a data focus; strong Python and SQL; hands-on experience with cloud data platforms (AWS and/or GCP), data warehouses (Snowflake, Redshift, or BigQuery), orchestration tools (Airflow or similar), and transformation tools (dbt preferred); healthcare data experience (FHIR/HL7, EHR APIs); data modeling expertise; clear communication. NYC-based: based in New York and in-office 3+ days per week. Compensation target: $170-$250k, plus equity and a generous benefits package. Thesi