Lead Data Engineer

You’ll take full ownership of data at a healthtech company with millions of lives to impact — setting architecture, choosing tools, and building the entire data platform from scratch.

You’ll be the first Data Engineer at a nationally scaling healthtech company, backed by leadership and trusted to build it your way. No legacy systems, no hand-holding — just a clear vision and the space to make it real.

This is greenfield with support. You’ll design the data stack from scratch, with full autonomy and direct input into business strategy. Whether it's dbt, Spark, Snowflake or Lakehouse — you decide what fits. Your work won’t just serve analysts or dashboards; it’ll fuel every squad across the business, from product to care delivery to AI/ML.

And this isn’t a solo mission. You’ll mentor engineers, influence data best practices, and leave a lasting imprint on the company’s tech culture. With just two office days a week, you’ll have deep focus time to ship meaningful work — without the burnout.

What you’d be doing

• Design and build the entire data platform — architecture, tooling, pipelines, and warehousing
• Deliver scalable, future-ready infrastructure that powers analytics, data science, and ML
• Drive data strategy and work closely with squads across product, engineering, and operations
• Create clean, reusable data products to support self-serve analytics and decision-making
• Set standards, mentor junior engineers, and build a high-quality engineering environment

What you’d bring

• Experience designing modern data architectures from the ground up
• Deep hands-on knowledge of tools like dbt, Spark, Snowflake, Fivetran, Airflow, etc.
• Strong Python and SQL skills
• Comfort with data warehousing, data lakes, distributed systems, and BI tools (Looker, Tableau, Metabase, Mode)
• Ability to lead strategically and technically — from initial design to long-term scaling
• A mindset that applies engineering principles to data systems, with a passion for mentorship