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About the Role
Our product requires integrating diverse data, including insurance plans, provider information, and member data. We are seeking our first Data Engineer to establish a reliable and usable data foundation, owning systems for data ingestion, modeling, and accessibility across the company. This hands-on role involves making key architectural decisions, building initial systems, and exploring AI applications in data engineering.
Responsibilities
- Own systems for moving, transforming, organizing, and serving data, including data warehouse, ingestion/export infrastructure, orchestration, transformation/modeling tools, semantic layers, data catalogs, quality, and observability.
- Ingest and connect data from various sources like vendors, carriers, providers, government entities, customer systems, and internal applications, building workflows for complex and disparate data.
- Design canonical models for core concepts (plans, networks, providers, etc.), preserving historical state, lineage, and provenance to ensure data trustworthiness.
- Make curated data available for backend systems, member/employer experiences, AI agents, brokerage workflows, CRM, reporting, and operational tools.
- Apply AI models and agents to automate data acquisition, interpretation, reconciliation, and quality investigation.
- Collaborate across teams to identify high-leverage data capabilities, prioritize the roadmap, and define infrastructure needs.
Requirements
- Experience building and operating production data systems across ingestion, warehousing, orchestration, modeling, quality, and serving.
- Hands-on proficiency in SQL and Python.
- Ability to turn broad goals into actionable work and manage projects from design to production.
- Experience with data from external organizations, understanding temporal modeling, idempotency, schema evolution, lineage, and provenance.
- Ability to make sound technical decisions without overbuilding.
- Experience designing data systems that support applications, automated workflows, customer-facing experiences, and business operations.
- Ability to work across disciplines with engineers, operators, and industry experts.
Skills
- Data Engineering
- SQL
- Python
- Data Warehousing
- Data Ingestion
- Data Transformation
- Data Modeling
- Orchestration
- Data Quality
- Data Observability
- AI in Data Engineering
- Schema Evolution
- Temporal Modeling
- Idempotency
- Lineage
- Provenance
Location
- San Francisco
Work Type
- In-person
Experience Level
- Zero-to-one builders
- First Data Engineer
About the Company
- Reimagining healthcare purchasing and navigation with an AI-native platform.
- Replacing traditional brokerages to streamline the healthcare process.
- Aiming to redefine how healthcare is bought and managed in America.
- A fast-growing, well-funded seed-stage startup incubated at General Catalyst.
- Composed of top talent from leading tech and brokerage firms.