Analytics Engineer

About Us

Lupa is building a category defining product the industry has never seen before.

We’re the AI-native operating system for veterinary practices and pet parents, replacing the fragmented, clunky systems vets have tolerated for years with a single intelligent platform for scheduling, client communication, clinical documentation, and AI-driven care guidance. Practices run more efficiently, vets get back to doing what they love, and pet parents feel more connected to their animals’ health than ever.

The traction speaks for itself: one of Europe’s top 100 AI startups with a team of 50 people, 10x growth in twelve months, the UK market leader, and now charging hard into the US and Europe. We have $25M in funding, 1M+ pets on the platform, and a buzzing HQ in Paddington, London.

This is a rare chance to join a rocket ship at exactly the right moment and we’re looking for exceptional people to help us fly it.

In this role, you will:

Own the analytics layer of our data platform; writing, structuring, and maintaining the SQL models that power dashboards, product metrics, and business intelligence across Lupa

Transform raw data from our platform into clean, reliable, well-documented datasets that Product, Engineering, and Commercial teams can actually use

Build and maintain reports that give the business a clear picture of clinical outcomes, practice performance, customer health, and growth metrics

Define and enforce data modelling best practices, including naming conventions, documentation standards, and testing coverage

Partner closely with the wider Data team to ensure analytics models sit on top of solid, well-engineered pipelines

Work directly with stakeholders across the business to understand what they need to know, translate that into clean SQL, and deliver answers that drive decisions

Your background looks something like:

2–3 years of hands-on experience in an analytics engineering, SQL engineering, or BI engineering role

Exceptional SQL skills, you write complex queries fluently, understand query optimisation, and care deeply about data model structure and readability

Solid experience with data modelling principles and building scalable, well-tested analytics layers (dbt experience strongly preferred)

Comfortable working with large, messy datasets and turning them into something clean, reliable, and trustworthy

Experience in a B2B SaaS, health-tech, or fast-growth startup environment (nice to have)

Familiarity with BI tooling such as Looker, Metabase, or similar (nice to have)

As a person, you:

Are proactive and self-structured, you create order in chaos and don’t need a rigid process to do great work

Communicate clearly and confidently with non-technical stakeholders, you can explain a data model to a sales lead without losing them

Take ownership of data quality as a first principle, if something looks wrong, you investigate and fix it, you don’t just flag it

Thrive in a fast-moving environment where the data landscape is constantly evolving as the product grows

Are excited to work in-person from our Paddington, London HQ

Value working with people who are kind, ambitious, and pragmatic

What does success look like in 6 months?

You own the analytics layer with confidence, models are clean, documented, tested, and trusted across the business

Stakeholders come to you first when they need to understand what’s happening in the data, because they know you’ll give them a straight answer

You’ve made a visible impact on how the business uses data to make decisions