Time Type:
Full time
Working Pattern:
Hybrid
Purpose of the Role
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. This position is suited to someone with demonstrable experience in the data analytics field with familiarity of the insurance sector being advantageous.
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
Skills, Knowledge and Experience
Essential
- 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
Desirable
- 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
AEGIS Values
Fairness and respect
We make decisions considering the best interests of key stakeholders. We are direct and straightforward in our actions, working collaboratively to create a culture of fairness and respect.
Open and inclusive
We act with integrity, valuing diversity of thought and background. We take time to listen to the needs of our customers, stakeholders and colleagues working together to seek and share information.
Ambitious
We have a passion for success, aspiring to be recognised as best in class. We embrace new opportunities, encouraging innovation in pursuit of our goals.
Striving to be better
We strive to improve at all times, challenging complacency, being agile and adapting to change. We always seek to improve our customers’ experience with us.
Investing in people’s potential
We provide an environment where each employee can reach their personal potential. We encourage personal accountability for performance and individual ownership for growth and success.
AEGIS London is an equal opportunities employer and recognises the value of a diverse workforce in facilitating better decision making and business growth. We encourage a variety of differing views, perspectives and insights to create a collaborative working environment. Diversity and Inclusion are fundamental to our business and we encourage applications from all backgrounds recognising the diversity of society and our customers.
It’s important to us that you are able to perform at your best when applying for a role with AEGIS London. If there are any adjustments we can reasonably make to ensure that the process is accessible for you please telephone us on +44(0)20 7856 7856 or email recruitment@aegislondon.co.uk
As a business, we understand individual circumstances may differ and aim to be adaptable and to support flexible working practices. Talk to our recruitment team to understand how AEGIS London can help support you in reaching your full potential
