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- Tasks: Build and maintain data pipelines for pricing analytics in a dynamic insurance environment.
- Company: A modern, digital-first home insurance provider focused on data-driven solutions.
- Benefits: Competitive salary, hybrid work model, and opportunities for professional growth.
- Other info: Autonomous role with collaboration across diverse teams and excellent career advancement potential.
- Why this job: Join a passionate team and make a real impact on data-driven decision-making.
- Qualifications: Strong SQL and Python skills, with experience in ETL/ELT pipelines.
The predicted salary is between 85000 - 85000 £ per year.
A modern, data-led, digital-first home insurance provider is seeking a talented Data Engineer to build and maintain the data foundations powering pricing analytics and underwriting performance. You do not need to have pricing specific experience, more the data engineering skills.
Role Overview
This is a highly autonomous, technically-focused role for someone passionate about data, code, and outcomes. You will design, build, and scale modular, end-to-end data pipelines, ensuring data quality, consistency, and scalability. Collaborating with Pricing, Underwriting, Data Science, and Engineering teams, you will enable smarter, faster decision-making by providing accurate, reliable, and timely pricing insights.
Key Responsibilities
- Own and evolve the data platform and pipelines for pricing analytics.
- Implement governance, validation, and alerting to ensure data integrity and reliability.
- Consolidate and modularise code for reusable, maintainable data components.
- Support batch processing for re‑priced datasets to deliver timely pricing and underwriting insights.
- Collaborate with teams to align on engineering standards and best practices.
- Streamline processes and enhance the scalability of the pricing data ecosystem.
Requirements
- Strong experience in SQL and Python (or similar object-oriented language).
- Proven experience designing and managing ETL/ELT pipelines.
- Meticulous attention to detail with a focus on data accuracy and process reliability.
- Self‑starter with strong problem‑solving, analytical, and communication skills.
Highly Advantageous
- Experience with cloud platforms (e.g., Azure, AWS, or GCP).
- Familiarity with PySpark or other big data technologies.
- Understanding of version control (e.g., Git).
- Knowledge of pricing or modelling workflows and how engineering choices impact them.
Senior Data Engineer - London -£85,000 - Hybrid - Insurance employer: Ascentia Partners
Contact Detail:
Ascentia Partners Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Data Engineer - London -£85,000 - Hybrid - Insurance
✨Tip Number 1
Network like a pro! Reach out to your connections in the insurance and data engineering fields. Attend meetups or webinars, and don’t be shy about asking for introductions. We all know that sometimes it’s not just what you know, but who you know!
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your data pipelines and projects. Use GitHub to share your code and document your processes. This gives potential employers a taste of what you can do and sets you apart from the crowd.
✨Tip Number 3
Prepare for those interviews! Research the company and its data practices. Be ready to discuss how you can contribute to their pricing analytics and underwriting performance. We want you to demonstrate your passion for data and problem-solving during those chats!
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we love seeing candidates who are proactive and engaged. So, don’t hesitate – hit that apply button and let’s get you on board!
We think you need these skills to ace Senior Data Engineer - London -£85,000 - Hybrid - Insurance
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your data engineering skills, especially in SQL and Python. We want to see how your experience aligns with the role, so don’t be shy about showcasing relevant projects or achievements!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you’re passionate about data and how you can contribute to our team. Keep it concise but engaging – we love a good story!
Showcase Your Problem-Solving Skills: In your application, give examples of how you've tackled challenges in previous roles. We’re looking for self-starters who can think on their feet, so let us know how you’ve made an impact through your analytical skills.
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’s super easy – just a few clicks and you’re done!
How to prepare for a job interview at Ascentia Partners
✨Know Your Data Engineering Basics
Make sure you brush up on your SQL and Python skills before the interview. Be ready to discuss your experience with ETL/ELT pipelines and how you've tackled data quality issues in the past. This role is all about data, so showing your technical prowess will definitely impress.
✨Showcase Your Problem-Solving Skills
Prepare examples of how you've solved complex data problems in previous roles. Think about specific challenges you faced and how you approached them. This will demonstrate your analytical mindset and ability to think critically, which are key for this position.
✨Familiarise Yourself with Cloud Platforms
Since experience with cloud platforms like Azure, AWS, or GCP is highly advantageous, make sure you can talk about any relevant projects you've worked on. If you haven't used these platforms extensively, do some research and be ready to discuss how you would approach using them in this role.
✨Collaboration is Key
This role involves working closely with various teams, so be prepared to discuss your experience collaborating with others. Highlight any instances where you aligned engineering standards or improved processes through teamwork. This will show that you're not just a tech whiz but also a great team player.