Build and own Snout’s data foundation, including PostgreSQL and dbt warehouses, ingestion pipelines, dimensional models, data quality, documentation, and reliable rebuilds. Reconcile data from veterinary practice-management systems, support LLM/AI tooling, translate stakeholder needs into technical plans, and establish the foundation for a future data team and analyst.
🐶 Our mission
🚀 The opportunity
💻 The role
🛠 What you’ll do
💡What we're looking for
🌟 What will make you stand out
💖 Why you should join Snout
❌ Why this role might not be a fit for you
💸 Compensation
⚕️Benefits
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.
🛠 What you’ll do
- 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 datasets from multiple source systems and turning them into something coherent
- A pragmatist’s bias toward simplicity — you reach for the simplest thing that works, can justify every tool and layer you’d add, and can tell the difference between complexity that earns its keep and complexity that doesn’t
- Strong communication: you can make a clear recommendation, back it with reasoning and cost, and commit wholeheartedly to a decision even when it isn’t the one you argued for
- Comfortable being the first and only data person for a while — self-directed, and happy building the foundation before there’s a team
- Experience as an early or first data hire who later grew a function or team
- Python (or similar) for pipelines and tooling
- Experience modeling data for LLM/AI consumption
- Familiarity with veterinary or healthcare data, or PIMS systems (Cornerstone, AllyDVM, etc.)
- Experience at a subscription or technology startup (Series A/B), on AWS
- Fast growing, venture capital backed technology company focused on improving access to veterinary care
- Ability to have a meaningful impact from Day 1, where your voice and opinion matters
- Unlimited potential to grow in your career, learn and expand your skillsets
- Collaborative, flexible, and friendly culture
- You believe every problem needs a new tool, and you’d want to stand up a large modern-data-stack (many SaaS tools, heavy infrastructure) before proving it’s needed — we optimize hard for simplicity and cost
- You’d rather be the analyst producing dashboards and insights than the engineer building the foundation those depend on
- You need an established data team and mature infrastructure around you to be productive
- A fast-moving startup culture feels overwhelming, or you’re uncomfortable with ambiguous, messy data from multiple source systems
- You prefer working in a silo rather than collaborating across GTM, CX, finance, and engineering
- You don’t live near an airport or have the flexibility to travel quarterly
- $165 000 - $185 000 base salary
- Equity
- Day 1 medical/dental/vision benefits
- Flexible time off + 11 Snout calendar holidays
- Paid parental leave
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