Data Engineer (Insurance OR Financial Services Background) - London - 75,000-85,000 - Hybrid

Data Engineer (Insurance OR Financial Services Background) - London - 75,000-85,000 - Hybrid

Data Engineer required to join a UK leading insurance business based in London. They are looking for someone who is happy to collaborate on a hybrid basis (1/2 days a week onsite). They offer excelllent career advancement alongside regular salary reviews.

Role Overview

This position is perfect for someone who takes pride in owning data, code, and outcomes. Youll play a central role in shaping and maintaining the data platforms and pipelines that drive pricing analytics and underwriting performance. Your work will ensure data quality, consistency, and scalability across the board. Partnering with teams across Pricing and Underwriting, Data Science, and Engineering, youll design and build modular, transparent pipelines - delivering end-to-end visibility from raw data ingestion to pricing model deployment, empowering smarter and faster decision-making.

Key Responsibilities

• Take ownership of, enhance, and scale the data platforms and pipelines that underpin pricing analytics.
• Implement robust governance, validation, and alerting systems to maintain data integrity, reliability, and responsiveness to changing data trends.
• Lead code consolidation and modularization efforts to create reusable, scalable, and maintainable data components that promote transparency and reproducibility.
• Oversee monthly batch processing to ensure the timely and accurate creation and ingestion of re-priced datasets for refreshed pricing and underwriting insights.
• Collaborate across teams to align engineering standards and promote best practices.
• Streamline processes to enhance efficiency and scalability across the pricing data ecosystem.

Skills:

Essential:

• A degree in Mathematics, Computer Science, Engineering, or a related discipline.
• Strong proficiency in SQL and Python (or another object-oriented programming language).
• Demonstrated experience in designing and managing ETL/ELT pipelines.
• Exceptional attention to detail, with a focus on data accuracy and process reliability.
• A proactive problem-solver with strong analytical and communication skills, capable of working both independently and collaboratively.

Desirable:

• Experience working with Azure (or other major cloud platforms).
• Familiarity with PySpark or other big data technologies.
• Understanding of version control systems (e.g., Git).
• Knowledge of pricing or modelling workflows and the impact of engineering decisions on model performance.

Why apply?

If you are looking to join a forward thinking, innovative and growing business who invests heavily in their peoples skills and progression this would be an excellent option!

Click Apply!