Data Engineer

Navina is a fast-growing digital health SaaS company that’s on a mission to transform the way physicians interact with patient data. Thousands of clinicians across the United States already use Navina’s AI-powered solution that transforms complex and fragmented patient data into concise “patient portraits" and actionable clinical insights at the point of care. With Navina, physicians experience less burnout, reduce missed diagnoses, and can devote more time giving better care to their patients.

Navina has been named one of the Top 100 AI companies globally by CB Insights and made the list of the Top 50 Digital Health startups. We are already working with industry-leading value-based organizations including Privia Health and Agilon.

Navina is looking for a talented and experienced Data Engineer to join our data group.

The team is responsible for processing and transforming data from multiple external sources while building and maintaining an internal serving platform. Our key challenges include operating at scale, integrating with diverse external interfaces, and ensuring the data is served in a consistent and reliable manner.

Responsibilities:

• Designing and implementing Navina’s data platform
• Transforming, modeling, and serving all Navina’s medical data.
• Utilize data best practices, to improve the product and allow data-driven decision-making.
• Collaborate closely with cross-functional teams to understand business requirements and translate them into data-driven solutions.
• Stay updated with the latest research and advancements in the data field.
  
  

• 5+ years of experience in software development, with at least 3 years as a data engineer.
• Proven track record designing and implementing scalable ETL/ELT data pipelines.
• Strong SQL skills.
• Experience with relational and analytical data platforms (e.g., PostgreSQL, Snowflake, data lakes).
• Strong coding skills (preferably in Python), with prior software engineering experience (e.g., API development) a plus.
• Experience with cloud environments, AWS preferable