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- Tasks: Build and maintain data pipelines for pricing analytics in a dynamic environment.
- Company: A modern, data-led home insurance provider focused on innovation.
- Benefits: Competitive salary, hybrid work model, and opportunities for professional growth.
- Other info: Collaborative culture with a focus on data quality and scalability.
- Why this job: Join a passionate team and make an impact with your data engineering skills.
- Qualifications: Strong SQL and Python skills; experience with ETL/ELT pipelines.
The predicted salary is between 75000 - 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.
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 modularize 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 scalability of the pricing data ecosystem.
- 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.
- 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 modeling workflows and how engineering choices affect model performance.
Data Engineer - London - £75,000-£85,000 - Hybrid employer: Ascentia Partners
Contact Detail:
Ascentia Partners Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Engineer - London - £75,000-£85,000 - Hybrid
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend meetups, and connect with potential colleagues on LinkedIn. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your data engineering projects, especially those involving SQL and Python. This will give you an edge and demonstrate your hands-on experience to potential employers.
✨Tip Number 3
Prepare for interviews by brushing up on common data engineering questions and scenarios. Practice explaining your thought process when designing ETL pipelines or ensuring data quality – it’s all about showing how you think!
✨Tip Number 4
Don’t forget to apply through our website! We’re always on the lookout for talented individuals like you. Plus, applying directly can sometimes give you a better chance of getting noticed by hiring managers.
We think you need these skills to ace Data Engineer - London - £75,000-£85,000 - Hybrid
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 pricing analytics. 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 data engineering. We’re looking for self-starters who can think critically, so share those moments where you made a difference!
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 how you've designed and managed ETL/ELT pipelines in the past. They’ll want to see that you can talk the talk when it comes to data quality and process reliability.
✨Showcase Your Problem-Solving Skills
Prepare examples of challenges you've faced in previous roles and how you tackled them. This role is all about autonomy and problem-solving, so demonstrating your analytical thinking will really impress them.
✨Familiarise Yourself with Their Tech Stack
If you know what cloud platforms they use, like Azure or AWS, make sure you mention any relevant experience you have. Even if you haven’t worked directly with their specific tools, showing that you understand the landscape can set you apart.
✨Collaborate and Communicate
Since this role involves working with various teams, be prepared to discuss how you’ve collaborated in the past. Highlight your communication skills and how you align engineering standards with other departments to drive better outcomes.