Head of Engineering (Data Platform)

Clover Health; United States; On-site; USD 150,000 - 180,000; Full time

Job summary

Clover Health in the United States is seeking a Head of Engineering, Data Platform to lead the strategic vision and execution of their data platform. This role requires a hands-on approach with technologies like Snowflake and DBT, and the ability to make key architectural decisions that support a modern, AI-driven data ecosystem.

The ideal candidate will blend technical acumen with team leadership, bringing significant experience in data platforms and a passion for crafting innovative data solutions.

Qualifications

• Proven experience in data platform architecture and strategy.
• Strong coding skills to contribute to platform builds and migrations.
• Experience managing cross-functional teams in a technology-driven environment.

Responsibilities

• Own the data platform strategy and execution, managing the architecture and tools.
• Design an AI-native data platform with advanced data pipelines.
• Make strategic decisions regarding tooling and vendor relationships.

Skills

Technical strategy

Snowflake

DBT

Data modeling

AI/NLP technologies

Job description

Our data platform powers one of healthcare's most ambitious technology transformations. We need a Head of Engineering, Data Platform to own it. This is a builder's role first. You'll set technical strategy and write the code that proves it out, working alongside a small, focused team and reporting directly to the Corporate CTO. The best person for this job still loves the craft, building alongside a small, engaged team of engineers. You'll bring a clear point of view on what a modern data platform should look like, the technical depth to make it real, and the leadership instincts to develop the team around you.

In this role you will:

• Own Platform Strategy & Execution
  • 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
• Drive AI-Native Data Platform
  • 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