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MOO is a sustainable print and merchandise company founded in 2004, now with 400+ employees and $1bn+ in lifetime revenue. The company operates globally with headquarters in London and offices across North America, South Africa, and Europe, serving half a million customers primarily in SMB segments.
The Data & Analytics team runs the platform integrating data from e-commerce, manufacturing, fulfillment, and finance systems. The tech stack is modern and warehouse-native: Snowflake, dbt, and Dagster, with a focus on building a governed semantic layer so trusted metrics are defined once and consumed everywhere—dashboards, self-service tools, and AI assistants.
In this Senior Analytics Engineer role, you will own analytical domains end-to-end. You'll define metrics in the semantic layer with stakeholders, build data models in dbt, and ensure KPIs resolve to the same trusted answer across all consumption points. Key responsibilities include:
- 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 BI tooling (currently Tableau) with a tool-agnostic mindset, reducing 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 toward fewer, better, trusted outputs
- Review others' work constructively and contribute to team modeling standards
- Demo new features and train business stakeholders as needed
You bring excellent communication skills, strong business acumen, and the ability to articulate complex technical concepts to non-technical stakeholders. You hold a practical, honest view of AI—enthusiastic about what governed, semantically-modeled data enables, but rigorous about validation and appropriately skeptical of new capabilities.
MOO offers 25 days holiday (rising by one day per year for 5 years), matched pension, paid parental leave, private healthcare, life insurance, season ticket loan, cycle-to-work scheme, and flexible/hybrid/remote working options including a Work From Anywhere program.
REQUIREMENTS:
- Strong SQL and production dbt experience
- Production experience on a cloud warehouse with Git-based, review-first workflows
- Track record of defining metrics with stakeholders and delivering outcomes people rely on
- Sound judgment about where logic should live (e.g., semantic layer vs. BI layer)
- Demonstrable interest in how data analytics is changing alongside AI, and commitment to developing your own skillset
NICE-TO-HAVES:
- Semantic layer tooling in production
- Natural-language/AI analytics tools (e.g., Cortex Analyst or similar) or experience preparing data for LLM consumption
- Experience rationalizing dashboard estates or migrating BI logic downstream
- E-commerce, manufacturing, or subscription business domain experience
