Senior Data Analyst

AEGIS London

Senior Data Analyst at AEGIS London delivering value-added analytics and commercial insights. Enhancing analytics workflows and modeling technical standards in a hybrid working environment.

Posted 5/3/2026full-timeLondon • 🇬🇧 United KingdomSeniorWebsite

Tech Stack

Tools & technologies

AzurePandasPythonSQL

About the role

Key responsibilities & impact

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 are embedded in day-to-day decision-making.
The Senior Data Analyst 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.

Requirements

What you’ll need

Significant experience in a data analytics or BI role with exposure in a Lloyd's syndicate, managing agent, London Market broker or specialty (re)insurer being advantageous
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
Python for data analysis (pandas / notebooks) and an appreciation of wider data science techniques, enough to collaborate credibly with Data Scientists and Actuarial
Hands-on experience applying AI / LLM tooling to analytics work (e.g. Copilot for Power BI / Fabric, MCP-style integrations, agentic assistants, code-generation tools) with a pragmatic view on where they add value
Experience with Microsoft Fabric, dbt, Azure DevOps / GitHub Actions, and data-quality tooling
Actuarial background

Benefits

Comp & perks

Fairness and respect
Open and inclusive
Ambitious
Striving to be better
Investing in people’s potential

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills & Tools

SQLPower BIDAXPower QueryPythondata analysisAI toolsdata modellingquery optimisationdata-quality tooling

Soft Skills

communication skillsstakeholder engagementpeer reviewconstructive feedbackproblem-solvingcollaborationanalytical thinkingteamworkattention to detailadaptability