Head of Engineering, Data Platform

Clover Health is reinventing health insurance by leveraging data and technology to improve healthcare outcomes. They are seeking a Head of Engineering for their Data Platform to own the technical strategy, lead a small team, and ensure the platform delivers significant business impact while embracing AI capabilities.

Responsibilities:

• Own the data platform end-to-end — architecture, tooling decisions, and roadmap — with a bias toward enabling broad, self-serve access to data across the business
• Be hands-on with Snowflake and DBT, contributing directly alongside the team on builds, migrations, and optimizations
• Integrate and rationalize a complex ecosystem of source systems and vendors into a cohesive, reliable data warehouse
• Define and evolve our approach to data modeling, including well-reasoned opinions on mart/gold layer design — when to enforce structure and when to get out of the way
• Make strategic build vs. buy decisions on tooling and vendor relationships, framing those decisions in terms of business and operational outcomes — not just technical elegance
• Design and evolve a data platform that is built for an AI-native organization — pipelines that serve LLM applications, infrastructure that supports agentic workflows, and tooling that compresses what used to take weeks into hours
• Use AI actively in your own workflow and bring strong opinions about where AI changes what a data platform needs to do and where it doesn’t
• Stay ahead of how AI is reshaping the role of data teams and translate that into concrete platform and staffing decisions
• Frame every platform decision in terms of business outcomes — operational efficiency, financial impact, clinical results. The data platform is a strategic enabler, not an isolated technical domain
• Partner with business stakeholders to translate data needs into platform capabilities without creating unnecessary friction or access barriers
• Make progress and tradeoffs visible to leadership as a natural byproduct of how you work
• Lead and develop a small high-impact team; setting a high bar for craft, communication, and ownership
• Think deliberately about team composition: what skills exist today, what gaps need to be filled, and how to sequence hiring to match the platform roadmap
• Invest in the growth of your team members, give clear feedback, create opportunities for ownership, and develop people who can grow with the platform

Requirements:

• An engineering background with deep, hands-on experience in Snowflake and DBT
• Proven experience navigating genuinely complex data environments and deeply heterogeneous source systems, messy integrations, inconsistent data models, and real business logic embedded in pipelines. The complexity of what you've worked with matters far more than the volume or scale
• A strong, well-reasoned point of view on data access philosophy; you believe raw data should be broadly available to business users and can defend why
• You have shipped AI-backed data systems and pipelines serving LLM applications, agentic workflows in data operations, or AI tooling that fundamentally changed what your team could do. Using Copilot for autocomplete is not the bar. You have opinions about where AI is reliable, where it isn't, and how it changes what a data platform needs to be
• Action-oriented on governance; you document what matters, automate what you can, and don't let process become a bottleneck
• Experience building and developing teams; you think about composition intentionally, hire for gaps, and invest in people's growth
• Exceptional communicator; you are clear, direct, and concise with both technical and non-technical audiences
• Cross-domain background is a plus; if you've built complex data platforms across different business contexts, that breadth is an asset. Experience in regulated domains (healthcare, financial services, etc.) is helpful but not required