Your teamThe 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 roleThis 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)
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