Lead Data Engineer

Nuna•San Francisco, CA

14d•$180,200 - $225,200

About The Position

Chronic disease isn't managed in a clinic. It is managed at home, in relationships, in the everyday. What's on the dinner table, what gets said, and who notices when someone's struggling. For the 130 million Americans managing a chronic condition, the healthcare system has offered the same answer for decades: a 15-minute doctor's visit, a pamphlet, and a portal login they'll never use. At Nuna, we are building an AI health coach that shows up like a person who actually has time: available at 3am, infinitely patient, and never behind a waiting room. We use motivational interviewing to help patients and their families see themselves clearly, design experiments that fit their real lives, and navigate a system that has not historically been on their side. We are building from the ground up around a simple belief: patients don't want to be healthy; they want their lives back. We're not competing with other health apps. We're competing with the moment a person gives up on getting better. If that's a problem you want to work on, we'd like to talk.

Requirements

Deep, hands-on expertise building and maintaining data platforms that support analytics and data science use cases
A track record designing robust ETL ingestion pipelines from external sources into a data platform
Experience setting standards for code development, deployment, and contribution in a data engineering environment
Strong command of data platform languages (Python, PySpark, and SQL)
The ability to translate fuzzy business and customer needs into clear requirements and an evaluation framework
Clear communication and presentation skills, whether the audience is scientists, engineers, or product partners
A genuine interest in improving healthcare alongside an interdisciplinary team
5–10 years of industry experience, including technical leadership of a data platform supporting business operations

Nice To Haves

You've built a data platform from zero to one before
You've worked with healthcare data
Degree in a quantitative field (data science, economics, statistics, engineering, or similar)
Experience with SDLC and managing machine learning models in production (MLOps)

Responsibilities

Own the architecture and evolution of the data platform, weighing trade-offs across timelines, cost, and resources
Build and optimize the transformations, pipelines, and datasets that power our analytics and data science work
Design and maintain integrations with external services
Define and enforce standards for how data engineering code gets developed, reviewed, and deployed
Establish security, governance, and operational best practices, in partnership with our security and enterprise data engineering teams
Provide build-vs-buy assessments as the platform expands, and surface new opportunities to improve it
Partner with engineering, design, product, and the wider Data org to turn business needs into working solutions