Data Analyst

Data Analyst, South West London (2/3 days per week), £65,000 - £75,000 per annum

What we're looking for:

As a Data Analyst you will work across a wide range of domains from financial and operational data, to tech and stock, helping our teams make better decisions grounded in sound analysis. As a curious problem-solver, you will be able to move between the technical and the commercial; and be comfortable building data models as well as presenting findings to senior stakeholders.

In this role you’ll work independently across the full data stack, understanding the ‘why’ behind requests before jumping to the ‘what’, and contributing to the translation of business problems into well-defined, actionable work. You’ll be supported by a collaborative team and won’t be expected to deliver everything solo from day one, but you’ll be expected to grow into doing so.

You will...

• Write and maintain SQL models (in Dataform) to transform and serve reliable data across our pipelines
• Support data engineers in the design, building and testing of data pipelines, able to contribute meaningfully, not just consume the output
• Build and iterate on cloud-based reports and dashboards in Looker (or similar BI tool), giving our support teams and restaurants clear, actionable insight into performance
• Translate business questions into well-scoped analysis and understand the problem and domain before reaching for the answer
• Communicate findings clearly to both technical and non-technical stakeholders, choosing the right medium for the audience
• Peer review colleagues’ work and contribute to data quality standards and documentation
• Identify opportunities to automate manual processes and data tasks, and take the initiative to implement them

Skills required

You will have proven experience in the following:

• Writing complex SQL to query, transform and model data across our cloud data platform (window functions, CTEs, complex datatypes)
• Building and maintaining data models in Dataform, or a similar data transformation tool such as Snowflake or DBT, with an understanding of how they fit into the broader pipeline
• Building reports and dashboards in Looker or a similar BI tool, serving reliable, self-serve data to the business
• Using Git as standard practice — branching, pull requests and code review
• Contributing to the translation of business requests into clearly scoped, actionable work items
• Applying data quality techniques — writing tests, identifying issues proactively and communicating data limitations clearly
• Documenting data models, definitions and lineage to a production standard
• Understanding data governance principles and championing good data management practice within the team
• Applying and understanding when to use relevant statistical methods to support analysis
• Supporting data engineers in designing, coding and testing data processing pipelines
• Using AI-assisted coding tools (e.g. Claude) to improve the speed and quality of your work — critically, not blindly — with an awareness of responsible AI use and data governance implications