Senior Analytics Engineer
HybridLondon, England, United Kingdom
Job Summary
Partner with stakeholders to translate ambiguous business needs into clear requirements and own the design of robust, scalable data models in dbt, Snowflake, and Looker. Set architectural standards and patterns for the team while leveraging AI-assisted development to focus on specifying intent and reviewing code rather than hand-writing boilerplate. Define and champion the trust infrastructure for testing, data contracts, and observability to ensure reliability across pipelines. Act as a technical anchor by conducting code reviews, mentoring peers, and driving continuous improvement of data platform tooling. Work remotely or hybrid across the UK and Europe, reporting to a senior leadership team focused on maximizing data value in the insurance sector.
Required Qualifications
- 5+ years' experience as an Analytics Engineer, or in a similar role
- expert SQL skills
- proven experience designing and owning data models for warehousing and BI — dimensional modelling, defining grain, and shaping the structure of a data domain from the ground up
- deep, hands-on experience with dbt
- experience with modern data platforms (e.g. Snowflake, Looker, AWS, GCP)
- experience with version control tools such as Git, and sound engineering practices around it
- meticulous eye for detail and strong problem-solving instincts
- track record of raising the standard around you — mentoring, reviewing, or setting the technical direction others follow
- genuine excitement about AI and how it changes our work — already using AI tools to work smarter, thinking critically about where they help and where they don't, and taking ownership of staying ahead
- strong commercial acumen — a real interest in the 'why' behind the numbers and the ability to connect data work to business outcomes
Desired Qualifications
- exposure to Python for data or analytics engineering tasks
- Experience in the insurance sector
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