Description:
Reporting to the Data Analytics Manager, the Senior Data Analyst is a hands-on individual contributor who helps the team through its shift from platform delivery (post-EDP) toward value-added analytics and commercial insight. The role contributes to building lasting data partnerships with the underwriting, claims and exposure management teams, so that analytics is embedded in day-to-day decision-making rather than delivered as isolated reports.
The role holder will apply and role-model the technical standards the team works to peer review, version control, documentation, testing and release management -and will aid the Data Analytics Manager to raise the overall maturity of the function. They will contribute to the most complex analyses and help introduce new techniques, including the practical application of AI tools within the analytics workflow.
Duties And Accountabilities
Business partnering and value-added analytics
- Act as the senior analytics business partner to one or more underwriting classes, proactively identifying where analytics can improve pricing, portfolio steering, renewal decisions and exposure management.
- Translate open-ended commercial questions into well-scoped analyses and dashboard requirements.
- Closely collaborate with the wider business to identify areas of automation and acceleration to improve operational efficiency.
- Identify practical opportunities to enhance the analytics workflow with AI tooling -for example, using LLMs and agentic tools for data exploration, code generation, documentation, and surfacing insight to underwriters.
- Support the Data Analytics Manager in shaping external data analytical propositions -from discovery and prototyping through to packaging and delivery.
Team maturity, standards and Power BI governance
- Apply and help embed the team’s development lifecycle for BI and analytics assets, including naming conventions, documentation, peer review and sign-off before production release.
- Follow and help maintain robust source-control practices for Power BI content – use of PBIP / TMDL format, Git-backed repositories, feature branches, pull requests and meaningful commit history.
- Contribute to Power BI workspace governance: clear Dev / Test / Prod separation, deployment pipelines, dataset certification / endorsement, refresh monitoring and access management.
- Coach analysts and BI developers on SQL, DAX, data modelling, visual design and engineering hygiene; take part in code / report reviews and knowledge-sharing sessions.
- Work closely with Data Engineering on changes to the semantic / curated layer and data marts, ensuring analytics and business needs are reflected in platform design.
- Deliver complex analytics workstreams end-to-end – scoping, estimation, delivery, hand-over and post-implementation review.
- Work within an Agile framework: break down requirements into epics and user stories, contribute to backlog prioritisation with the Data Analytics Manager, and provide realistic estimates.
Essential
Skills, Knowledge and Experience
- Well developed and demonstrable experience in a data analytics or BI role, preferably in an insurance or finance environment.
- Advanced SQL, including query optimisation and working with the Azure data stack (Data Factory, Synapse / Fabric, SQL-based semantic layers).
- Advanced Power BI: data modelling (star schemas), advanced DAX, Power Query / M, performance tuning, RLS, and deployment via pipelines.
- Understanding of Power BI engineering discipline: PBIP / TMDL source format, Git-based version control, pull-request review, structured release and rollback process; demonstrable experience of these practices in a team.
- Proven ability to carry out peer review and QA of analytics work – spotting model errors, DAX issues, performance problems and UX weaknesses, and giving constructive feedback.
- Excellent written and verbal communication skills, including presenting to underwriting and internal stakeholders.
- Strong stakeholder engagement, with a track record of turning ambiguous business problems into delivered analytical outcomes.