Analytics Engineering Manager

In a nutshell, we're all about making the world of wine a better place. We fund and source directly from independent winemakers to bring customers better quality wine for a better price. No thirsty middlemen as far as the eye can see.

It's a different way of doing things, sure. But it works. We're one of the UK's favourite wine clubs, shipping over 1 million (!) cases a year to curious wine lovers. And with an ambitious road ahead, we've got no plans on plugging the cork on growth.

Our global team (we have offices in the US and Australia, too) is entrepreneurial by nature, obsessive about customer experience and driven by performance. All things that make Naked a great place to grow both personally and professionally. And yes, we like wine. A lot.

It takes a village to be Naked. That's why we're always on the lookout for eager talent to join the club. And now we're looking for an Analytics Engineering Manager to join the fun.

We're building a unified intelligence layer so every metric, model, and AI agent works from the same governed source of truth. It's the foundation the business depends on to move with speed and confidence. As our Analytics Engineering Manager, you will own the semantic layer and the governed metrics that define how the business measures itself, translating stakeholder needs into clean, consistent data products built in partnership with our Data Engineering team.

We're moving fast to become an AI-native team and we want someone who's excited to work with us towards enabling this.

So if you're keen to help us take the guesswork out of enjoying great wine (that's what we're passionate about), there's a Naked welcome pack with your name on it. Together, we'll take Naked Wines to the next level - and share our not-so-well-kept secret with the world.

London or Norwich Office Hybrid Role (1 day a week in the office).

• Intelligence Layer Ownership
  :
  Shape our unified intelligence layer to ensure it is trusted by analysts and structured clearly enough for AI agents to query, reason over, and use reliably
• Semantic Governance
  :
  Define and govern the canonical metrics, dimensions, and business logic implementation that the entire company relies on for decision-making
• Model Design & Platform Migrations
  :
  Define robust modelling requirements behind major platform migrations, partnering closely with Data Engineering on what gets built and owning how it's exposed and consumed
• dbt Workflow Evolution
  :
  Collaborate on our dbt environment, contributing to model design, documentation, and testing, using dbt as our shared, single source of truth for business logic
• Strategic Bridge
  :
  Sit between the business and Data Engineering, translating complex stakeholder questions into clear modelling requirements and governed, self-serve metrics
• Platform Durability
  :
  Drive platform portability initiatives to ensure our data products are durable, scalable, and independent of any single technical stack
• Technical Review
  :
  Own the technical review process for metric and model changes before they reach production, partnering with the wider team on complex modelling challenges
• Roadmap Leadership
  :
  Shape and steer the long‑term Analytics Engineering roadmap to support a rapidly growing global e-commerce business.

• Experience
  : 4+ years of professional experience in Analytics Engineering or BI Engineering, with a proven track record of delivering clean data architectures
• Technical Proficiency
  :
  Strong working knowledge of dbt
  ; you have contributed to production dbt projects and can read, write, test, and document models with confidence
• AI Mindset
  :
  You already incorporate AI into your daily modelling, documentation, or review workflows and are excited to experiment with agentic workflows or multi‑step orchestration
• Domain Expertise
  :
  Essential experience in multi‑market or multi‑currency data modelling setups
• Cloud Infrastructure
  :
  Hands‑on experience with cloud‑based MPP warehouses (ideally Big Query or Redshift
  )
• Data Fundamentals
  : A deep understanding of data warehousing, dimensional modelling, and the rare ability to balance rigorous governance with pragmatic business speed
• Engine…