Own analytical domains end to end by defining trusted metrics, dimensions, and business logic in semantic models; building production dbt data models; and delivering reliable Tableau reporting. Partner with operations, commercial, finance, and supply chain stakeholders, validate governed datasets for AI consumption, reduce conflicting outputs, promote data literacy, review modeling work, and train stakeholders on new capabilities.
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. Not online but out there, in real life.
We started in 2004. Since then we’ve built an award-winning and much-loved brand, with customer satisfaction and Trustpilot ratings that make most businesses want to give up and hire an army of review bots. We’ve got half a million customers, mostly small and medium businesses in North America, the UK, and Europe – businesses that, like us, get all excited about putting something real and beautiful into people’s hands. Does that make us nerds? Probably, and we’re ok with that.
We’ve been given the highest business award in Britain, ‘The Queen’s Award for Enterprise’. Backed by venture capital, we’re part of Tech Nation’s ‘Future Fifty’, recently passing $1bn in lifetime revenue, and featuring in the Guardian’s top 10 UK start-ups list. Ok, we’ll stop bragging now.
Today, we’re more than 400 people with our global HQ in London, UK, while we also have premises in Dagenham. In the US, you’ll find us in Boston, MA, as well as East Providence, RI and Denver, CO and with our most recent office expansion in Cape Town 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 so trusted metrics are defined once and consumed everywhere: dashboards, self-service tools, and AI assistants.
We build on a modern, warehouse-native stack — Snowflake, dbt, and Dagster — and we're working towards a governed semantic layer so trusted metrics are defined once and consumed everywhere: dashboards, self-service tools, and AI assistants.
This role exists to own analytical domains end-to-end. Defining their metrics in the semantic layer with stakeholders, data modelling in dbt, and making sure a KPI resolves to the same trusted answer wherever it's consumed.
The person we want
You're an analytics engineer or data analyst with a rounded experience in data modelling and engineering practice.
You possess excellent communication skills, with the ability to articulate complex technical concepts to non-technical stakeholders.
You have strong business acumen and instinct, enabling you to challenge metric definitions to ensure they reflect real business outcomes
You hold an honest, practical view about AI. You're enthusiastic about what governed, semantically-modelled data makes possible, but rigorous about validation and approach new capability with a healthy skepticism (but not cynicism).
You possess excellent communication skills, with the ability to articulate complex technical concepts to non-technical stakeholders.
You have strong business acumen and instinct, enabling you to challenge metric definitions to ensure they reflect real business outcomes
You hold an honest, practical view about AI. You're enthusiastic about what governed, semantically-modelled data makes possible, but rigorous about validation and approach new capability with a healthy skepticism (but not cynicism).
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
What’s it like to work at MOO?
MOO’s the kind of workplace where you can really be yourself. Dye your hair purple. Hit the sofa with your laptop. Whatever helps you feel comfortable and happy at work. We want to help you grow in your career and set you up for success – while also 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 (for 5 years), a matched pension scheme, and paid parental leave. We’ll offer you private healthcare, life insurance, a season ticket loan, and a cycle to work scheme. We also offer flexible work schedules with hybrid and remote working for certain roles as well as a Work From Anywhere program.
Diversity Statement
We are working hard to create a representative, inclusive and super-friendly team, because we know that different experiences, perspectives and backgrounds make for a better workplace. And that creates a better experience for our customers. 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.
As a design and technology company we have a desire and a responsibility to build a business that represents the world around us. So we strive to create a values-driven, purposeful and highly empowered organisation that we are all proud to work for. And we are committed to continuous investment in building an open and inclusive environment, welcoming a diverse audience of candidates who see themselves working and thriving at MOO. Therefore, we’d like to invite you to complete this optional survey to help us evaluate our inclusion and diversity efforts. Completing this form is entirely voluntary and if you decide not to it won’t in any way affect your job application. We keep the information separate from your application and it is kept secure and confidential, it is only used to better our inclusion and diversity efforts. By submitting this information, you consent to MOO's processing of it for these purposes.
MOO London, England Office
Chalk Farm Road, LABS Triangle, The Stables Market, London, United Kingdom, NW1 8AB
MOO Dagenham, England Office
Thames Gateway Park Chequers Lane, Unit 12, Dagenham, United Kingdom, RM9 6FB
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