At Nuna, our mission is to make high-quality healthcare affordable for everyone. We are dedicated to tackling one of our nation’s biggest problems with ingenuity, creativity, and a keen moral compass.

Nuna is committed to simple principles: a rigorous understanding of data, modern technology, and most importantly, compassion and care for our fellow human. We want to know what really works, what doesn't—and why.

Nuna partners with healthcare payers, including government agencies, health plans, and self-insured employers, to turn data into learnings and information into meaning.

At Nuna Engineering, we build so that everyone can use, learn, and act. Our technology enables data scientists, analysts, benefits officers, and policymakers to understand healthcare data while ensuring its integrity, security and privacy. Our work runs the gamut, from joining multiple streams of messy real-world data to building queryable data warehouses to constructing visualizations and dashboards that provide actionable insight. We build systems that are auditable, as automated as possible, accurately represent the underlying data, and, most importantly, responsive to our end users' needs. We strive for a creative, collaborative engineering environment that implements best practices of peer review, readability, maintainability, and security of the code base and infrastructure.

The Nuna Analytics Platform team is Nuna’s small but rapidly growing frontend engineering team. We build Nuna’s user-facing web apps and the internal tools that enable our domain expert analysts to add rich features to those products on their own (and test them, too!). We work on top of Nuna’s Data Platform, turning a distributed SQL database into easy-to-use reporting tools, innovative data visualizations, and quickly digestible dashboards. We ensure enterprise-grade stability and startup-grade velocity by maintaining a well-tested code base and redeploying our infrastructure from scratch every release.

  • Enable instant, flexible, and usable reporting on terabyte-­sized data sets.
  • Build frameworks to enable internal analysts to build, test, and deploy entire products.
  • Work with User Experience Designers and User Researchers to understand our users (external and internal) and the problem space of unmet needs in healthcare data science.
  • Define and implement reusable, scalable UI components.
  • Implement, test, and deploy the product through its entire development lifecycle.
  • Be a mentor to junior engineers.
  • Enforce high-quality coding standards and practices via reviews and by demonstrating this in their own work.
  • Have a bias to action.
  • Be able to help others break down large team goals into specific and manageable tasks.
  • Be involved and supportive of agile sprint model of development, helping to enforce the practice and the discipline.
  • Able to work efficiently and proactively across engineering teams to enable us to deliver on our goals of loosely coupled, adaptable, scalable solutions.

Skills and responsibilities

  • Experience building production-hardened frontend servers, with consideration for security, performance, scalability, reliability, and repeatability. Familiarity with web frameworks like Django, Go’s web packages, etc.
  • Experience sustainably engineering Javascript applications.
  • Knowledge of database fundamentals; experience debugging and optimizing SQL queries.
  • Experience managing production servers and designing smooth deployment processes.
  • Be an excellent communicator.
  • Deal well with ambiguity and act with autonomy.
  • 4+ years of experience in this or a related field.
  • Technology-agnostic and pragmatic sensibility; focused on solving key problems, not the tools.
  • Knowledge of computer science fundamentals (such as debugging and object-oriented design) and software engineering processes (such as agile project management).
  • Demonstrated ability to understand automated testing concepts and ability to consistently apply those concepts.
Bonuses include...
  • Experience building tools for data analysis or data analysis platforms.
  • Experience with data visualization.
  • Experience architecting Javascript applications.
  • Experience building enterprise frontends.
  • Experience building mobile web application experiences.

Technologies Used At Nuna
  • Python, Java, Go, R, SQL, Django
  • JavaScript, Typescript, React, Webpack, Jekyll
  • Spark, Presto, Crunch, and Hadoop
  • Linux, OS X & Windows
  • AWS; including EC2, EBS, RedShift, EMR, ELB, SNS, RDS, CloudFormation, and more


  • Location:
    San Francisco
  • Deadline:


Minimum qualifications