Founding Data Engineer

Every pet should get the care they need, regardless of cost. Vet med prices are up 40% since 2020, and pet owners are stuck having to pick between their bank account and furry friend. At Snout, we aim to solve this by enabling clinics to offer pet wellness plans, that actually work.

Snout is one of the fastest growing wellness plan providers in the veterinary space, trusted by clinics across the U.S. We’re a small but mighty startup team. We’re looking for a remote, U.S. based Founding Data Engineer to build the data foundation the rest of the company will run on.

This is Snout’s first dedicated data hire, reporting directly to the CTO. You’re inheriting a real, working system — a Postgres operational database and a dbt-modeled analytics warehouse that already powers internal reporting and our LLM/AI tooling — but one that’s grown faster than anyone’s had time to organize. Your job is to turn it into a firm, documented, trustworthy foundation.

That means first understanding what data we actually have and where it lives, then making it coherent. We ingest hundreds of millions of rows from multiple veterinary practice-management systems (Cornerstone, AllyDVM, and others) alongside our own application data — today the same concept can live in several places with different shapes, and part of your early work is reconciling those lineages into definitions people can trust.

From there you’ll own and extend the warehouse, harden the pipelines and the nightly rebuild, and shape a model that makes analysis fast and reliable.

You’ll do the up-front work of a founding hire: talk to stakeholders across the company, understand what they need, present options and clear recommendations with their trade-offs and cost, and then execute on the path we choose. We’re hiring a data analyst after you — you’ll set them up to succeed and be the technical backbone they lean on. Do this well and you put Snout in a genuinely data-driven position and grow a team underneath you.

Snout is committed to building a diverse and inclusive team. We know that great candidates may not check every box — and that’s okay. If you're excited about this role and our mission, we encourage you to apply if you meet at least 75% of “what we’re looking for” including the first bullet point. If you need any accommodations during the application or interview process, please let us know — we’re happy to support you.

• Map Snout’s data landscape end to end — what exists, where it lives, what’s canonical vs. stale — and document it so it’s no longer tribal knowledge
• Reconcile data from multiple source systems (application data + multiple PIMS ingests) into conformed, trustworthy models where a term like “appointment” or “invoice” means one thing
• Own and extend our dbt warehouse: model the source-system activity that isn’t modeled yet, and raise the bar on tests, documentation, and data freshness
• Own the ingestion pipelines and the warehouse rebuild — keep them reliable, and recommend where to simplify or consolidate
• Keep clean, well-modeled data flowing to the tools that consume it, including our internal LLM/AI tooling
• Run early discovery with stakeholders across GTM, CX, finance, and product; turn business questions into a build plan; present options with clear trade-offs and cost before executing
• Set up and support the data analyst we hire next — be the technical foundation they build analysis on

• 6+ years building and maintaining production data systems as a data or analytics engineer
• Deep SQL and hands‑on PostgreSQL experience
• Strong dbt and dimensional/data-modeling experience in production — you’ve built warehouses people actually trust
• A track record of taming large, messy…