At a Glance
- Tasks: Drive impactful data analytics and collaborate with teams to enhance decision-making.
- Company: Join AEGIS London, a forward-thinking company valuing diversity and innovation.
- Benefits: Enjoy a hybrid work model, competitive salary, and opportunities for personal growth.
- Other info: Embrace a culture of fairness, respect, and continuous improvement.
- Why this job: Make a real difference by applying advanced analytics and AI in a dynamic environment.
- Qualifications: Experience in data analytics, strong SQL skills, and familiarity with Power BI required.
The predicted salary is between 55000 - 65000 € per year.
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.
Senior Data Analyst in London employer: AEGIS London
AEGIS London is an exceptional employer that fosters a collaborative and inclusive work culture, prioritising fairness and respect among its diverse workforce. With a strong commitment to employee growth, the company offers ample opportunities for professional development in the dynamic field of data analytics, particularly within the insurance sector. Located in London, AEGIS provides a hybrid working model that supports flexibility, allowing employees to thrive both personally and professionally while contributing to innovative analytics solutions.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Data Analyst in London
✨Tip Number 1
Network like a pro! Reach out to your connections in the data analytics field, especially those in the insurance sector. A friendly chat can lead to insider info about job openings that aren't even advertised yet.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your best analytics projects, especially those involving Power BI and SQL. This will give potential employers a taste of what you can bring to the table.
✨Tip Number 3
Prepare for interviews by brushing up on common data analytics questions and scenarios. Practice explaining complex analyses in simple terms, as you'll need to communicate effectively with stakeholders.
✨Tip Number 4
Don't forget to apply through our website! It’s the best way to ensure your application gets noticed. Plus, we love seeing candidates who are proactive about their job search.
We think you need these skills to ace Senior Data Analyst in London
Some tips for your application 🫡
Tailor Your Application:Make sure to customise your CV and cover letter to highlight your experience in data analytics, especially in the insurance sector. We want to see how your skills align with the role of Senior Data Analyst, so don’t hold back on showcasing relevant projects!
Showcase Your Technical Skills:Since this role requires advanced SQL and Power BI skills, be sure to include specific examples of how you've used these tools in your previous roles. We love seeing practical applications of your technical expertise, so let us know how you’ve tackled complex analyses!
Communicate Clearly:Your written communication skills are key for this position. When crafting your application, aim for clarity and conciseness. We appreciate well-structured documents that make it easy for us to understand your thought process and achievements.
Apply Through Our Website:We encourage you to submit your application through our website. It’s the best way for us to receive your details and ensures you’re considered for the role. Plus, it gives you a chance to explore more about our company culture and values!
How to prepare for a job interview at AEGIS London
✨Know Your Data Inside Out
Before the interview, dive deep into your past data analytics projects. Be ready to discuss specific examples where you used SQL and Power BI to solve complex problems. Highlight how your insights led to tangible business outcomes, especially in the insurance sector.
✨Showcase Your AI Savvy
Since the role involves applying AI tools, brush up on your knowledge of how you've integrated AI into your analytics workflow. Be prepared to discuss practical applications, like using LLMs for data exploration or code generation, and how these innovations improved efficiency.
✨Master the Art of Communication
Strong communication skills are key for this position. Practice explaining complex analytical concepts in simple terms. Think about how you would present your findings to underwriting teams and ensure you can articulate the value of your analyses clearly.
✨Emphasise Collaboration and Stakeholder Engagement
This role requires close collaboration with various teams. Prepare examples that demonstrate your ability to work with stakeholders, turning ambiguous questions into actionable insights. Show how you've built strong partnerships in previous roles to drive analytics initiatives.
