At a Glance
- Tasks: Own and evolve the Data Lake infrastructure and ETL pipelines from day one.
- Company: Join a fast-growing fintech redefining consumer lending with innovative AI solutions.
- Benefits: Equity ownership, hybrid work, 25 days holiday, and wellness budget.
- Other info: Enjoy a collaborative culture with opportunities for personal and professional growth.
- Why this job: Make a real impact on data-driven decision-making in a dynamic environment.
- Qualifications: Strong software engineering skills and experience with AWS and data systems.
The predicted salary is between 60000 - 80000 € per year.
About Abound
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.
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
Data Engineer employer: Abound
At Abound, we are not just redefining consumer lending; we are creating a dynamic and inclusive work environment where innovation thrives. As a Data Engineer, you will enjoy the benefits of equity ownership, a hybrid work model, generous holiday allowances, and unique wellness initiatives that promote team bonding and personal growth. Join us in our mission to make finance fairer while advancing your career in one of Europe's fastest-growing fintechs, backed by top-tier investors and a commitment to employee development.
StudySmarter Expert Advice🤫
We think this is how you could land Data Engineer
✨Tip Number 1
Network like a pro! Reach out to current employees at Abound on LinkedIn or other platforms. Ask them about their experiences and any tips they might have for landing a role as a Data Engineer. Personal connections can make a huge difference!
✨Tip Number 2
Prepare for the interview by brushing up on your technical skills. Make sure you can confidently discuss your experience with AWS, SQL, and data pipelines. Practice common data engineering problems and be ready to showcase your problem-solving abilities.
✨Tip Number 3
Showcase your projects! If you've worked on relevant data engineering projects, create a portfolio or GitHub repository to share during your interview. This will demonstrate your hands-on experience and passion for the field.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you’re genuinely interested in joining the team at Abound.
We think you need these skills to ace Data Engineer
Some tips for your application 🫡
Tailor Your CV:Make sure your CV reflects the skills and experiences that align with the Data Engineer role. Highlight your experience with AWS, SQL, and data pipelines to show us you’re the right fit!
Craft a Compelling Cover Letter:Use your cover letter to tell us why you’re excited about joining Abound. Share specific examples of how your past work has prepared you for this role and how you can contribute to our mission.
Showcase Your Projects:If you've worked on relevant projects, don’t hesitate to mention them! Whether it’s a personal project or something from your previous job, we love seeing practical applications of your skills.
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 without any hiccups!
How to prepare for a job interview at Abound
✨Know Your Tech Stack
Familiarise yourself with the technologies mentioned in the job description, especially AWS, Spark, and SQL. Be ready to discuss your hands-on experience with these tools and how you've used them to build or optimise data systems in the past.
✨Showcase Your Problem-Solving Skills
Prepare examples of how you've tackled challenges in previous roles, particularly around data pipelines and infrastructure. Highlight your ability to redesign data structures for improved performance and cost efficiency, as this aligns with what they’re looking for.
✨Understand Their Business Model
Research Abound’s approach to consumer lending and their use of AI and Open Banking data. Being able to articulate how your role as a Data Engineer can contribute to their mission will show that you’re genuinely interested in the company and its goals.
✨Emphasise Collaboration
Since the role involves partnering closely with the Data Science team, be prepared to discuss your experience working cross-functionally. Share examples of how you've collaborated with other teams to achieve common goals, demonstrating your adaptability and teamwork skills.
