Senior Analytics Engineer
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.
The person we want
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
Skills
As published by lever · 5 questions · 3 written answers
Basics
Resume/CV, Full name, Pronouns, Email, Phone, Current location, Current company, LinkedIn URL, Twitter URL, GitHub URL, Portfolio URL, Other website, What is your age range?, I identify my ethnicity asIn England and Wales, there are 18 ethnic groups recommended for use by government. These are grouped into 5 broad ethnic groups, with an ‘Any other’ option where respondents can write in their ethnicity using their own words, What gender do you identify as?
Pick from a list (2)
- Are you legally authorized to work in the UK
- Will you now or in the future require sponsorship for an employment visa?
Written answers (3)
- As this is a hybrid role are you able to be onsite in Camden 2 days a week?
- As part of our process and to ensure alignment early on, could you please share your salary expectations for this role? This helps us save time and ensure we are aligned on compensation expectations.
- What is your current notice period or earliest availability to start? optional