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- Tasks: Design and implement modern cloud-based data platforms for the London Insurance Market.
- Company: Join a leading firm transforming data solutions in the insurance sector.
- Benefits: Hybrid working model, competitive salary, and opportunities for career growth.
- Other info: Collaborate with senior leaders and work on innovative AI-driven analytics projects.
- Why this job: Make a real impact on critical transformation initiatives using cutting-edge technology.
- Qualifications: Proven experience in data engineering with strong skills in Python, PySpark, and cloud platforms.
The predicted salary is between 60000 - 80000 £ per year.
We are hiring an experienced Senior Data Engineer to join a high-impact transformation programme focused on modernizing data platforms within the London Insurance Market. This is an excellent opportunity to work on cloud-native solutions that power underwriting, pricing, claims, reinsurance, regulatory reporting, and AI-driven analytics.
You will play a key role in designing scalable data architectures, building robust pipelines, and partnering with senior stakeholders across business and technology functions.
Working Model: Hybrid
- Design and implement modern cloud-based data platforms using Medallion Architecture.
- Build and optimize batch and real-time data pipelines across underwriting, pricing, claims, reinsurance, and bordereaux data.
- Develop scalable solutions using Python, PySpark, Databricks, and/or Snowflake.
- Integrate data from policy administration systems, claims platforms, broker systems, third-party providers, and market feeds.
- Ensure strong data quality, reconciliation, lineage, governance, and auditability.
- Support analytics, MI, regulatory reporting, and AI use cases.
- Apply AI-assisted engineering tools (Open AI / Claude) to improve delivery productivity.
- Drive engineering best practices including code reviews, CI/CD, Git workflows, and automated testing.
Proven experience as a Senior Data Engineer or Lead Data Engineer. Deep knowledge of underwriting, claims, delegated authority, pricing, and reinsurance. Hands-on expertise in Python, PySpark, Databricks, Snowflake, SQL. Experience with Azure, AWS, or GCP. Strong understanding of batch/streaming pipelines and data modelling. Familiarity with DevOps practices, CI/CD, and Git-based delivery models. Work on business-critical transformation initiatives. Collaborate with senior leaders across Data, Underwriting, Finance, and Actuarial teams. Use modern cloud and AI technologies. Strong career growth in a specialist market domain.
If you have the right blend of Data Engineering expertise and Insurance domain knowledge, we’d love to hear from you.
Senior Engineer, Data Engineering employer: Axiom Software Solutions Limited
Contact Detail:
Axiom Software Solutions Limited Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Engineer, Data Engineering
✨Network Like a Pro
Get out there and connect with folks in the industry! Attend meetups, webinars, or even local events related to data engineering and insurance. The more people you know, the better your chances of landing that dream job.
✨Show Off Your Skills
Don’t just talk about your experience; demonstrate it! Create a portfolio showcasing your projects, especially those involving Python, PySpark, or cloud platforms. This will give potential employers a taste of what you can bring to the table.
✨Ace the Interview
Prepare for technical interviews by brushing up on your coding skills and understanding data architectures. Practice common interview questions and be ready to discuss how you've tackled challenges in previous roles. Confidence is key!
✨Apply Through Us
We’ve got your back! Apply directly through our website for the best chance at landing that Senior Data Engineer role. We’re always on the lookout for talent like yours, so don’t hesitate to reach out!
We think you need these skills to ace Senior Engineer, Data Engineering
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with cloud-native solutions and data engineering. We want to see how your skills in Python, PySpark, and Databricks align with our needs in the London Insurance Market.
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Tell us why you're passionate about data engineering and how your background in insurance can add value to our transformation programme. Keep it engaging and relevant!
Showcase Your Projects: If you've worked on any cool projects involving data pipelines or cloud platforms, make sure to mention them. We love seeing real-world applications of your skills, especially if they relate to underwriting or claims.
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 this exciting opportunity in our hybrid working model!
How to prepare for a job interview at Axiom Software Solutions Limited
✨Know Your Tech Stack
Make sure you’re well-versed in the technologies mentioned in the job description, like Python, PySpark, and Snowflake. Brush up on your knowledge of cloud platforms such as Azure, AWS, or GCP, and be ready to discuss how you've used these tools in past projects.
✨Understand the Insurance Domain
Since this role is focused on the London Insurance Market, it’s crucial to have a solid understanding of underwriting, claims, and pricing. Familiarise yourself with industry-specific terms and challenges, so you can speak confidently about how your experience aligns with their needs.
✨Prepare for Scenario-Based Questions
Expect questions that assess your problem-solving skills and technical expertise. Prepare examples of how you’ve designed scalable data architectures or optimised data pipelines. Use the STAR method (Situation, Task, Action, Result) to structure your responses effectively.
✨Showcase Collaboration Skills
This role involves working closely with senior stakeholders across various teams. Be ready to share examples of how you’ve successfully collaborated with others, driven engineering best practices, and contributed to business-critical initiatives in your previous roles.