Senior Analytics Engineer

MOO is all about making great design available to everyone. We do that by producing premium print and branded merchandise. But it’s as much about how we do it, leading with design, technology and sustainability.

Founded in 2004, we’ve come this far by being obsessed with the happiness of our customers. Along the way, we’ve built an award-winning and much-loved brand, with exceptional customer satisfaction and Trustpilot ratings. Those customers are typically small and medium-sized businesses based in North America, the UK, and Europe – businesses that, like us, value design and see the brand-building power of putting something real in people’s hands.

We’ve received the highest business award in Britain, ‘The Queen’s Award for Enterprise’. Part of Tech Nation’s ‘Future Fifty’, we’ve been profiled in the Financial Times, and ranked in the Guardian’s top 10 UK start-ups.

Today we are over 350 people, headquartered in the UK but with many of our people based in the USA and South Africa.

The person we want

Responsibilities

Partner with stakeholders across operations, commercial, finance, and supply chain to design data models and unlock analytic capabilities

Define metrics, dimensions, and business logic in the semantic layer (dbt Semantic Layer / Snowflake semantic views)

Deliver reporting through our BI tooling (currently Tableau) with a tool-agnostic mindset, and reduce duplicated or conflicting outputs.

Curate and validate governed datasets and semantic models for AI/natural-language consumption, acting as the accuracy bar for AI-generated analysis.

Champion healthy self-service and data literacy heading in the directon of fewer, better, trusted outputs

Review others' work constructively and contribute to the team's modelling standards.

Demo new features and train business stakeholders when required

About you

Strong SQL and production dbt experience

Production experience on a cloud warehouse with Git-based, review-first workflows

A track record of defining metrics with stakeholders and delivering outcomes people rely on

Can demonstrate sound judgement about where logic should live - e.g. in semantic layer or BI layer

Demonstrable interest in how data analytics is changing alongside AI, and developing own skillset

Nice to have's

Semantic layer tooling in production

Natural-language/AI analytics tools (e.g. Cortex Analyst or similar) or preparing data for LLM consumption.

Experience rationalising dashboard estates or migrating BI logic downstream

E-commerce, manufacturing, or subscription business domains