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AAbound
London, United Kingdom7 months ago
Work format
Hybrid
English level
B2, upper-intermediate
An email or a Telegram message to the recruiter
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.
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
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
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.
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