At a Glance
- Tasks: Join our team to build and enhance data-driven applications and pipelines.
- Company: Dynamic reinsurance company focused on innovation and collaboration.
- Benefits: Professional development, hybrid work options, and a vibrant inclusive culture.
- Other info: Great opportunities for career growth and hands-on experience.
- Why this job: Make a real impact in data engineering while working with talented colleagues.
- Qualifications: Experience in data engineering or related fields; Python skills preferred.
The predicted salary is between 63000 - 77000 £ per year.
We are looking for a technically minded and collaborative Data Engineer to join our growing Data & Insights practice within Global Specialties.
Responsibilities:
- Help deliver data and technology solutions from concept through implementation as part of a growing team.
- Build, enhance, and maintain data-driven applications, pipelines, and unified data models.
- Apply your data engineering expertise to improve the quality, structure, accessibility, and usability of data.
- Work with actuaries, analysts, business stakeholders, and technical teams to understand their requirements and translate them into practical data solutions.
- Review existing data flows, models, processes, and applications, identifying opportunities to improve performance, consistency, and scalability.
- Help address challenges relating to legacy applications, unstructured data, and decentralized data storage.
- Contribute to data transformation initiatives and the development of a stronger data engineering centre of excellence.
- Explain technical concepts clearly and help stakeholders make informed decisions about their data and technology.
- Challenge existing approaches constructively, helping teams improve the way they define, manage, and use data.
- Contribute to product- and project-oriented delivery, helping to shape priorities, define outcomes, and deliver value incrementally.
- Collaborate with and share best practices across engineering teams at Marsh Re.
- Support an agile delivery culture through experimentation, feedback, frequent releases, and continuous improvement.
Requirements:
- Experience in a data engineering, software engineering, analytics engineering, data modelling, or similar technical role.
- Experience working with insurance, reinsurance, broking, actuarial, or other financial services data, with an understanding of the terminology, processes, and business context.
- A strong understanding of data structures, data modelling principles, data flows, and data transformation.
- Previous experience writing code, with the ability to understand, review, and contribute to production-quality code.
- Expertise in Python backend frameworks, ideally Django, FastAPI, or Flask.
- The ability to work confidently with both technical and non-technical stakeholders.
- Strong communication and collaboration skills, including the confidence to explain, challenge, and influence.
- A pragmatic approach to problem-solving, with the ability to balance technical quality, business needs, and delivery timelines.
- Some experience of product management, project delivery, or product-oriented ways of working.
- The confidence and curiosity to walk into an unfamiliar conversation, ask the right questions, and help move the discussion forward.
- A willingness to work hands-on while also engaging with the wider business and helping shape longer-term data capabilities.
We are not necessarily looking for someone with extensive experience. We would welcome applications from candidates who have built a strong technical foundation and are ready to broaden their experience across stakeholder engagement, product delivery, and data strategy.
Desirable:
- Experience working with insurance, reinsurance, broking, or specialty market data.
- An understanding of reinsurance transactions, portfolio management, risk appetite, or insurance purchasing processes.
- Previous experience writing code, with the ability to understand, review, and contribute to production-quality code.
- Expertise in Python backend frameworks, ideally Django, FastAPI, or Flask.
- The ability to work confidently with both technical and non-technical stakeholders.
- Strong communication and collaboration skills, including the confidence to explain, challenge, and influence.
- Some experience of product management, project delivery, or product-oriented ways of working.
- The confidence and curiosity to walk into an unfamiliar conversation, ask the right questions, and help move the discussion forward.
- A willingness to work hands-on while also engaging with the wider business and helping shape longer-term data capabilities.
Conditions:
We help you be your best through professional development opportunities, interesting work and supportive leaders. We foster a vibrant and inclusive culture where you can work with talented colleagues to create new solutions and have impact for colleagues, clients and communities. Our scale enables us to provide a range of career opportunities, as well as benefits and rewards to enhance your well-being. Marsh is committed to hybrid work, which includes the flexibility of working remotely and the collaboration, connections and professional development benefits of working together in the office. All Marsh colleagues are expected to be in their local office or working onsite with clients at least three days per week. Office-based teams will identify at least one "anchor day" per week on which their full team will be together in person.
Data engineer in reinsurance in London employer: Marsh
Marsh is an exceptional employer that fosters a dynamic and collaborative work culture, where innovation thrives and employees are empowered to make impactful contributions. With a strong focus on professional development, team members have access to numerous growth opportunities while working in a hybrid environment that balances flexibility with in-person collaboration across various UK locations. Joining Marsh means being part of a forward-thinking team dedicated to delivering cutting-edge AI solutions in a supportive and inclusive atmosphere.
StudySmarter Expert Advice🤫
We think this is how you could land Data engineer in reinsurance in London
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We think you need these skills to ace Data engineer in reinsurance in London
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
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Craft a Tailored Cover Letter:For a full-time role at Marsh, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Marsh. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at Marsh
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
✨Showcase Your Projects
Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at Marsh!
✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
