Senior Analytics Engineer
Role Overview
Own analytical domains end to end, defining trusted metrics with stakeholders and modelling data in dbt.
Help ensure each KPI resolves to the same trusted answer across dashboards, self-service tools, and AI assistants.
Work with a warehouse-native stack including Snowflake, dbt, and Dagster while supporting a governed semantic layer.
Key Skills for This Role
Full Job Posting
About MOO
MOO combines design, technology, manufacturing, and service to produce print and merchandise products.
MOO has more than 400 people, with its global headquarters in London and other premises and international offices.
The data team supports e-commerce, manufacturing, fulfilment, and finance systems.
Role overview
Own analytical domains end to end, defining trusted metrics with stakeholders and modelling data in dbt.
Help ensure each KPI resolves to the same trusted answer across dashboards, self-service tools, and AI assistants.
Work with a warehouse-native stack including Snowflake, dbt, and Dagster while supporting a governed semantic layer.
The person we want
- Experience as an analytics engineer or data analyst with data modelling and engineering practice.
- Excellent communication skills for explaining complex technical concepts to non-technical stakeholders.
- Strong business acumen and judgement to challenge metric definitions against business outcomes.
- A practical and appropriately sceptical approach to AI and governed, semantically modelled data.
- Strong SQL and production dbt experience.
- Production experience with a cloud warehouse and Git-based, review-first workflows.
- Track record of defining metrics with stakeholders and delivering reliable outcomes.
- Sound judgement about where logic should live, such as the semantic layer or BI layer.
- Demonstrable interest in analytics changes driven by AI and in developing personal skills.
Responsibilities
- Partner with operations, commercial, finance, and supply chain stakeholders to design data models and unlock analytics.
- Define metrics, dimensions, and business logic in the dbt Semantic Layer or Snowflake semantic views.
- Deliver Tableau reporting with a tool-agnostic mindset and reduce duplicated or conflicting outputs.
- Curate and validate governed datasets and semantic models for AI and natural-language consumption.
- Champion self-service and data literacy focused on fewer, better, trusted outputs.
- Review work constructively, contribute to modelling standards, demo features, and train stakeholders.
Nice to have
- Production experience with semantic layer tooling.
- Experience with natural-language or AI analytics tools such as Cortex Analyst, or preparing data for LLM consumption.
- Experience rationalising dashboard estates or migrating BI logic downstream.
- Experience in e-commerce, manufacturing, or subscription business domains.
Workplace information
- MOO offers flexible work schedules with hybrid and remote working for certain roles, plus a Work From Anywhere programme.
- The description does not specify which workplace arrangement applies to this role.
Benefits
- MOO offers holiday increasing to 30 days after five years, a matched pension scheme, and paid parental leave.
- Benefits include private healthcare, life insurance, a season ticket loan, and a cycle to work scheme.
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