Data Architect
Confirmed live in the last 24 hours
Nomi Health

201-500 employees

Affordable direct healthcare services & solutions
Company Overview
Nomi Health’s mission is to rewire how we pay for healthcare and how it is delivered to provide affordable and accessible healthcare experiences we all deserve as employers, patients and providers. The company is rebuilding healthcare from the ground up, simplifying how healthcare is understood, paid for and delivered through a real-time, direct infrastructure.
Data & Analytics

Company Stage

Series B

Total Funding





Orem, Utah

Growth & Insights

6 month growth


1 year growth


2 year growth

Austin, TX, USA
Experience Level
Desired Skills
Data Science
Data Analysis
Data Engineering
Data Management
Data & Analytics
  • Bachelor’s or Master’s degree in Computer Science, Data Engineering, or a related field
  • 5 - 10 years experience as a data engineer with a focus on modeling, SQL, NoSQL, and system architecture
  • Strong proficiency in Python and experience with data processing frameworks
  • Experience with code reviews, version control, and continuous integration/continuous deployment (CI/CD)
  • Excellent problem-solving skills and attention to detail
  • Strong communication skills to convey technical concepts to diverse audiences
  • Previous experience in a senior or lead data engineering role
  • Understanding of data governance and compliance
  • Evolving infrastructure, patterns, and tooling with a focus on high throughput, reliable, and idempotent pipelines
  • Ensuring the business receives, processes, and transmits high-quality data for data science and reporting needs
  • Designing and owning data models for product application and analytical models
  • Building and maintaining efficient and scalable data models to meet business requirements
  • Working closely with cross-functional teams to understand data needs and drive alignment with business objectives
  • Architecting and building robust and scalable data systems to support organizational growth
  • Evaluating and recommending appropriate technologies for different components of the data infrastructure
  • Establishing and enforcing data engineering standards, coding conventions, and best practices
  • Playing a key role in establishing a data governance framework and committee to enable and empower the organization in leveraging data assets
  • Developing and maintaining data pipelines built on top of variations of Python & SQL
  • Creating clear and comprehensive documentation, including data models, architecture diagrams, and data workflows
  • Mentoring members of the data engineering team and providing guidance on best practices