At a Glance
- Tasks: Drive impactful data analytics and collaborate with teams to enhance decision-making.
- Company: Join a forward-thinking insurance company that values innovation and teamwork.
- Benefits: Enjoy a competitive salary, flexible working options, and opportunities for personal growth.
- Other info: Dynamic work environment with a strong focus on diversity and inclusion.
- Why this job: Be at the forefront of analytics, using AI tools to shape the future of insurance.
- Qualifications: Proven experience in data analytics, especially within the insurance sector.
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 employer: AEGIS
At AEGIS London, we pride ourselves on being an exceptional employer that fosters a culture of fairness, respect, and inclusivity. Our hybrid working model allows for flexibility while providing ample opportunities for professional growth and development in the dynamic field of data analytics. With a commitment to innovation and collaboration, we empower our employees to reach their full potential and contribute meaningfully to our mission in the insurance sector.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Data Analyst
✨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 opportunities 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 do before they even meet you.
✨Tip Number 3
Prepare for interviews by brushing up on common data analytics scenarios. Think about how you’d tackle real-world problems using AI tools or advanced SQL techniques. We want to see your thought process!
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, we love seeing candidates who take the initiative to connect directly with us.
We think you need these skills to ace Senior Data Analyst
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 mention specific tools and techniques you've used. We love seeing examples of your work, so if you’ve got any dashboards or analyses you can share, do it!
Communicate Clearly:Your written communication skills are key for this position. When writing your application, keep it clear and concise. We appreciate a straightforward approach, so make sure your passion for data analytics shines through without unnecessary fluff.
Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it gives you a chance to explore more about what we do at StudySmarter!
How to prepare for a job interview at AEGIS
✨Know Your Data Inside Out
Before the interview, dive deep into your past projects and experiences related to data analytics. Be ready to discuss specific examples where you used SQL, Power BI, or AI tools to solve complex problems. This will show your hands-on experience and ability to translate commercial questions into actionable insights.
✨Showcase Your Collaboration Skills
Since the role involves working closely with underwriting and claims teams, prepare to discuss how you've successfully partnered with different stakeholders in the past. Highlight instances where your analytical insights led to improved decision-making or operational efficiency, demonstrating your value as a business partner.
✨Demonstrate Technical Proficiency
Brush up on your technical skills, especially in SQL and Power BI. Be prepared to answer questions about query optimisation, data modelling, and version control practices. You might even be asked to solve a problem on the spot, so practice explaining your thought process clearly and confidently.
✨Embrace the Agile Mindset
Familiarise yourself with Agile methodologies, as this role requires breaking down requirements into epics and user stories. Be ready to discuss how you've contributed to backlog prioritisation and provided realistic estimates in previous roles. Showing that you can adapt and thrive in an Agile environment will set you apart.
