Senior Analytics Engineer

MOO brings brands to life in a sustainable way, with a range of remarkable print and merchandise products. We combine design, technology, manufacturing, and service, so that people can connect in memorable ways. We started in 2004 and have built an award-winning brand with high customer satisfaction ratings. Today, we’re more than 400 people with our global HQ in London, UK, and additional offices in the US and South Africa.

We're a team of data engineers and analytics engineers running the platform that brings together data from our e-commerce, manufacturing, fulfilment, and finance systems. We build on a modern, warehouse-native stack — Snowflake, dbt, and Dagster — and we're working towards a governed semantic layer for trusted metrics.

This role exists to own analytical domains end-to-end, defining metrics in the semantic layer with stakeholders, data modelling in dbt, and ensuring KPIs resolve to the same trusted answer wherever they're consumed.

The person we want:

• You're an analytics engineer or data analyst with rounded experience in data modelling and engineering practice.
• You possess excellent communication skills, able to articulate complex technical concepts to non-technical stakeholders.
• You have strong business acumen, enabling you to challenge metric definitions to ensure they reflect real business outcomes.
• You hold a practical view about AI, enthusiastic about governed, semantically-modelled data while being rigorous about validation.

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.
• C curate and validate governed datasets and semantic models for AI/natural-language consumption.
• Champion healthy self-service and data literacy heading towards 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 reliable outcomes.
• 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.

Nice to have's:

• Semantic layer tooling in production.
• Natural-language/AI analytics tools (e.g. Cortex Analyst or similar).
• Experience rationalising dashboard estates or migrating BI logic downstream.
• E-commerce, manufacturing, or subscription business domains.

What’s it like to work at MOO?

MOO’s the kind of workplace where you can really be yourself. We want to help you grow in your career and set you up for success while recognising the importance of a healthy work/life balance. That’s why we offer 25 days holiday rising by one day for each year here, a matched pension scheme, and paid parental leave. We also offer flexible work schedules with hybrid and remote working for certain roles.

Diversity Statement:

We are working hard to create a representative, inclusive, and friendly team, because we know that different experiences, perspectives, and backgrounds make for a better workplace. MOO doesn’t discriminate on the basis of race, colour, religion or belief, gender, national origin, age, sexual orientation, marital status, disability or any other protected class.