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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 with a digital-first approach.
- Benefits: Competitive salary of £85,000, hybrid work model, and opportunities for professional growth.
- Other info: Collaborative culture with a focus on innovation and scalability.
- Why this job: Join a passionate team and make an impact on data-driven decision-making.
- Qualifications: Strong SQL and Python skills, experience with ETL/ELT pipelines, and attention to detail.
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 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.
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 modeling workflows.
Data Engineer - London -£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 -£85,000 - Hybrid
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend meetups, and connect with fellow data enthusiasts. 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 projects, especially those involving SQL and Python. This gives potential employers a taste of what you can do and sets you apart from the crowd.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and problem-solving skills. Practice common data engineering scenarios and be ready to discuss how you've tackled challenges in past projects.
✨Tip Number 4
Don't forget to apply through our website! We make it easy for you to find roles that match your skills and interests. Plus, it shows you're genuinely interested in joining our team!
We think you need these skills to ace Data Engineer - London -£85,000 - Hybrid
Some tips for your application 🫡
Tailor Your CV: Make sure your CV reflects the skills and experiences that match the Data Engineer role. Highlight your SQL and Python expertise, as well as any experience with ETL/ELT pipelines. We want to see how you can contribute to our data-driven environment!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Share your passion for data and coding, and explain why you're excited about this role at StudySmarter. Let us know how your background aligns with our mission to enhance pricing analytics and underwriting performance.
Showcase Your Projects: If you've worked on relevant projects, don’t hold back! Include links or descriptions of your work that demonstrate your ability to build and maintain data pipelines. We love seeing practical examples of your skills in action!
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 shows us you’re keen to join the StudySmarter team!
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 to share specific examples of challenges you've faced in previous roles and how you overcame them. Think about times when you had to ensure data integrity or streamline processes. This will demonstrate your analytical mindset and ability to think on your feet.
✨Familiarise Yourself with the Company’s Tech Stack
Do a bit of homework on the cloud platforms they use, like Azure or AWS, and any big data technologies mentioned in the job description. If you have experience with PySpark or version control systems like Git, be sure to highlight that during your chat.
✨Collaborate and Communicate
Since this role involves working with various teams, be prepared to discuss how you've collaborated in the past. Share examples of how you’ve aligned with different departments to achieve common goals. Strong communication skills are key, so don’t shy away from showcasing your teamwork abilities.