Engineering Manager

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 to 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’s Data Platform is the backbone of our product, powering how data flows from the outside world into our AI-driven clinical insights. As Engineering Manager (Data Platform), you will own this critical layer end-to-end - leading multiple teams responsible for acquiring, transforming, and serving healthcare data at scale.

This role combines people leadership, technical ownership, and strategic influence. You will lead the teams that ingest data from diverse external sources (EMRs, HIEs, external Snowflake instances and more), transform it into Navina’s core data structures, and reliably serve it to internal and external consumers across the company.

As an architectural owner of one of Navina’s most critical assets, you will work closely with Product, Engineering, Medical, AI, and Support teams, and play a key role in shaping Navina’s R&D leadership and long-term growth.

Requirements:

Proven experience leading multiple engineering teams with a strong track record of growing people and helping them succeed
Startup mindset - comfortable with ambiguity, fast growth, and evolving processes, while understanding what’s needed to scale sustainably
Strong technical orientation and curiosity, with the ability to quickly learn new domains and technologies and develop long term vision for the architecture , process and structure of the team
Experience leading large, cross-team technical initiatives end-to-end
Excellent communication and stakeholder management skills

Nice to Have

Experience building or operating large-scale data platforms
Familiarity with healthcare data ecosystems (EMRs, HIEs, clinical data)
Experience working in AI-driven or data-heavy products

You don’t need to meet 100% of the requirements to be a great fit. We believe in hiring people, not just checklists, and we value potential as much as experience. If this role excites you, we’d love to see your application!

Responsibilities:

People Leadership

Lead, grow, and support multiple data teams (currently two teams), creating an environment where people thrive professionally and personally
Hire top talent and build strong team structures that can scale with the company
Coach, mentor, and up-level managers and senior engineers, fostering ownership and accountability
Promote a culture of excellence, collaboration, and continuous learning

Technology & Architecture

Own Navina’s data platform end-to-end: ingestion, transformation, storage, and serving layers
Connect business and product needs with pragmatic, scalable technical solutions
Drive architectural decisions that balance speed, quality, reliability, and long-term maintainability
Ensure the data platform supports both current products and future growth

Cross-Company Leadership

Lead complex, cross-team technical initiatives involving Product, Engineering, AI, Medical, and Support
Serve as a key interface between data teams and the rest of the organization
Be a thought partner to product and business leaders on data capabilities and trade-offs

R&D Management

Be an active member of Navina’s R&D leadership team
Help define priorities, execution plans, and best practices as Navina scales
Contribute to company-wide technical and organizational decisions

AI-First Mindset

Drive adoption of an AI-first approach to building, running, testing, maintaining, and documenting systems
Encourage the use of AI tools and practices to increase team efficiency, quality, and innovation
Help redefine how data platforms are built and operated in an AI-native company