At a glance
- Employment
- Full-time
- Workplace
- Hybrid
- Location
- London
About the role
- We're looking for an Analytics Engineer to help build and maintain the data models that power analytics and data science across the business.
- You'll develop robust, scalable dbt pipelines and help evolve our data platform — ensuring data is accessible, trusted, and well-structured.
- This is also a role built around AI-assisted development, using AI tools as a normal part of writing dbt models, tests, and docs.
Responsibilities
- Build and maintain dbt models, using AI coding assistants to accelerate development while retaining full understanding of the resulting logic
- Translate business requirements into scalable data models
- Design warehouse schemas using dimensional modelling (facts, dimensions, SCDs, etc.)
- Participate in design and code reviews — including reviewing AI-generated code with the same rigour as hand-written code
- Define and expose models and metrics through our semantic layer, with an eye to how AI agents will consume them via MCP
- Implement dbt tests for data quality and accuracy
- Document models and metric definitions clearly, for both human and AI consumption
- Use GitHub and CI/CD pipelines, incorporating AI-assisted workflows where they add value
- Optimise dbt models and SQL queries for performance and maintainability
- Work with Snowflake on top of a data lake architecture
Requirements
- Strong experience building and optimising complex SQL (joins, window functions, optimisation)
- Strong grasp of data modelling and warehouse design (Kimball-style)
- Production dbt experience, including testing and documentation
- Hands-on experience using AI coding tools (e.g. Copilot, Cursor, Claude Code) as a real part of your workflow, not occasional use
- Strong-enough fundamentals to work confidently without AI assistance and to critically assess AI-generated output
- Familiarity with version control (GitHub)
- Able to independently translate business logic into technical implementation
- Comfortable giving and receiving code review
Preferred qualifications
- Snowflake experience
- Semantic layer experience (e.g. Omni, Cube, dbt Semantic Layer)
- BI tools (e.g. Omni, Tableau, Metabase)
- Exposure to AI agent tooling / MCP
- CI/CD for data workflows
- Python/Airflow familiarity
- Terraform / IaC
Benefits
- 27 days holiday, plus 5 additional days off (1 life event day, 2 volunteer days, 2 company-wide wellbeing days, and 8 bank holidays per year)
- Private medical insurance with Bupa
- Medical cashback scheme
- Life insurance
- Gym membership and wellness resources through Wellhub
- Access to Spill mental health support
Workplace
- Hybrid work offering with collaboration in the office three days per week for most roles
Skills
- SQL
- Dbt
- GitHub
- Snowflake
- Omni
- Cube
- Tableau
- Metabase
- Python
- Airflow
- Terraform
- Copilot
Show all 14 skills
- Cursor
- Claude Code
