Lead Data Engineer

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.

Your team

The data team at Nuna is an interdisciplinary group spanning data science, machine learning, data analytics, actuarial science, and research. Within it, data engineering is the technical backbone which creates the architecture, platform, and operations that everything else is built on.

You'll work shoulder to shoulder with both scientists and engineers, on a team led by a data scientist. That means the platform you build isn't an abstraction: it serves real modeling, research, and analytics needs, and you'll see exactly who depends on it and why.

The role

This is a foundational, hands-on role for someone who wants to build a data platform from zero to one and shape its direction as Nuna grows. You'll own the architecture and make the calls on standards, build-vs-buy, and trade-offs — often with incomplete information and the freedom to define the right answer yourself. Comfort with ambiguity isn't a nice-to-have; it is the job.

What you’ll do

• 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

What we’re looking for

• 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

Bonus Points

• 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)

Nuna is an Equal Employment Opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, age, disability, genetics and/or veteran status.

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