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Salary
$74k – $138k per year (Estimated)
Location
Remote/Hybrid (London, United Kingdom)
Seniority
Senior
Employment
Full-Time

Confirmed on the employer's own hiring board on Sep 23, 2026. First seen by Alion on Sep 18, 2026. Moo scores B on the Alion truth index.

Overview
Company
Impact
Profile match

Moo

MOO is an online print and design company that enables you to bring your ideas to life. With a focus on providing great design for everyone, MOO offers a wide range of products and services to cater to your printing needs. Their flagship product, Original Business Cards, sets a new standard for standard business cards with its thicker, high-quality design. MOO also offers Business Cards with special finishes, such as Spot Gloss, Gold Foil, and Silver Foil, to add extra dazzle and texture to your cards. In addition to business cards, MOO offers a variety of other print products, including Postcards, Flyers, Stickers & Labels, and Stationery. They also provide customized options, such as Change of Address Cards, Gift Certificates, and Custom Notebooks. If you're looking to elevate your branding, MOO offers branded products like Custom MOO Water Bottles and Business Card Holders. And for businesses in need of extra support and services, MOO offers revamped plans with premium benefits. With a passion for helping people design the best looking, quality products, MOO is a trusted partner for businesses of all sizes. Get inspired by the MOO community and unlock the power of custom print w

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.

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).

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
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