Data Engineer – Data Modelling & Insights

We are looking for a technically minded and collaborative Data Engineer to join our growing Data & Insights practice within Global Specialties.

This is an opportunity to play a central role in improving how we collect, structure, manage, and use data across the global reinsurance market. Working closely with our Lead Data Engineer and a wide range of senior stakeholders, you will help develop data-driven applications, pipelines, and unified data models covering reinsurance transactions, market trends, and purchasing behaviour.

The role will suit someone with a background in data engineering, software engineering, analytics, or a related technical discipline who is also comfortable working directly with stakeholders. You will spend time with actuaries, analysts, business leaders, and technical teams to understand how they work with data, identify opportunities for improvement, and help shape more effective data models and solutions.

You will need to be confident explaining technical concepts, challenging existing approaches constructively, and leading conversations with senior colleagues even when entering an unfamiliar or challenging environment. You will help stakeholders understand what their data models and processes need to deliver, where they may be falling short, and how they can be improved.

Our ambition is to empower colleagues to provide comprehensive advice and help clients make well-informed decisions regarding their reinsurance purchasing, risk appetite, and portfolio management across London.

We embrace agile ways of working, focusing on experimentation, frequent delivery, feedback, and close collaboration with stakeholders.

This is a full-time position based in our London office, with the successful candidate expected to work from the office three days per week.

We will count on you to:

• 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 a Marsh Re.

• Support an agile delivery culture through experimentation, feedback, frequent releases, and continuous improvement.

What you need to have:

• 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.

What makes you stand out?

• 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.
• 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.

Why join our team:

• 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 (NYSE: MRSH) is a global leader in risk, reinsurance and capital, people and investments, and management consulting, advising clients in 130 countries. With annual revenue of over $27 billion and more than 95,000 colleagues, Marsh helps build the confidence to thrive through the power of perspective. For more information, visit marsh.com, or follow us on LinkedIn and X.

Marsh is committed to embracing a diverse, inclusive and flexible work environment. We aim to attract and retain the best people and embrace diversity of age background, civil partnership status, disability, ethnic origin, family duties, gender orientation or expression, gender reassignment, marital status, nationality, parental status, personal or social status, political affiliation, race, religion and beliefs, sex/gender, sexual orientation or expression, skin color, or any other characteristic protected by applicable law. We are an equal opportunities employer. We are committed to providing reasonable adjustments in accordance with applicable law to any candidate with a disability to allow them to fully participate in the recruitment process. If you have a disability that may require reasonable adjustments, please contact us at reasonableaccommodations@marsh.com.

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.