Abound
From Abound's careers page
Status: listed on the employer's own careers page when we last checked (daily). Confirm on their site before applying.
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.
We’re redefining consumer lending in the UK, and beyond. Using advanced AI and Open Banking data, we make fair, affordable personal finance available to more people. While traditional lenders rely almost entirely on credit scores, we look at the full financial picture - how much you spend, and what you can afford to repay to build a deeper, more accurate understanding of each customer's unique financial situation.
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.
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
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
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
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
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