Data Engineer

And we've shown it works at scale. We’ve issued over £1.3bn in loans directly to customers while delivering market-leading credit performance - for every 10 defaults the industry expects, we see only 3. We also reached profitability just 2.5 years after launch.

Backed by £2bn+ of funding from top-tier investors including Citi, GSR Ventures, and Deutsche Bank, we’re recognised as one of Europe’s fastest-growing fintechs (Sifted, CNBC). Now, we’re expanding into new markets and product lines - and we’re looking for ambitious people who want to learn fast, take ownership, and grow with us. About the Role As a Data Engineer within the Platform team, you will play a critical role in maturing and optimizing our Data Lake. Acting as a key bridge between Platform and Data Science, you will take ownership of the infrastructure and pipelines that power data-driven decision-making across the business. This is an Individual Contributor (IC) role with high impact and autonomy. In your first 6–12 months, your primary focus will be to evolve the Data Lake into a scalable, high-performance foundation for analytics and data science. You will migrate key production workloads- such as model calibration, ad-hoc analytics, and reporting- directly into the Data Lake, while redesigning data structures to improve query performance, reduce AWS costs, and ensure high data recency. You will also establish yourself as a trusted partner to the Data Science team, enabling faster experimentation and delivery through robust, well-designed data systems. Technology Stack Cloud & Compute: AWS, ECS Fargate, AWS Lambda Databases & Data Lake: Aurora (PostgreSQL, MySQL), Athena, DMS, Glue, Iceberg Languages & IaC: Python, Spark, SQL Observability & Tooling: Amazon Managed Prometheus (AMP), incident.io, GitLab What you'll be doing Own and evolve the Data Lake infrastructure and ETL pipelines from day one Migrate production workloads (e.g. model calibration, ad-hoc analytics, reporting) into the Data Lake Partner closely with Data Science to understand workflows and enable scalable, efficient data usage Redesign data structures and clustering strategies to improve query performance and data freshness Optimize infrastructure to reduce AWS costs while maintaining reliability and scalability Build robust, production-grade data systems using modern AWS tooling Who you are Strong software engineering foundation with applied knowledge of SOLID principles in data systems Proven experience building and maintaining Change Data Capture (CDC) pipelines, ideally with AWS DMS Hands-on expertise with Spark and AWS Glue, including transforming RDS workloads into scalable pipelines Highly proficient in SQL, particularly within transactional RDS environments Experience implementing governance, standards, and best practices across data platforms Comfortable owning systems end-to-end and working cross-functionally with technical stakeholders How we work Ownership: You take responsibility for outcomes, not just tasks Impact-Driven Work: You focus on results and step up during critical moments when needed MVP Mindset: You prioritize speed and learning, accepting and managing technical debt when appropriate Collaboration: You go beyond your role and avoid siloed thinking Adaptability: You thrive in a fast-moving environment with shifting priorities Pragmatism: You value sound judgment and lightweight processes over rigid bureaucracy What we offer Everyone owns a piece of the company - equity Hybrid with 3 days a week in the office 25 days’ holiday a year, plus 8 bank holidays 2 paid volunteering days per year One month paid sabbatical after 4 years Employee loan Free gym membership Team wellness budget to be active together - set up a yoga class, a tennis lesson or go bouldering