At a Glance
- Tasks: Join our team to enhance data quality and support credit decisions using modern analytics tools.
- Company: Lendable, a fast-growing fintech revolutionising consumer finance in the UK and US.
- Benefits: Flexible working, competitive salary, and opportunities for professional growth.
- Other info: Collaborative environment with experienced engineers and regular social events.
- Why this job: Be part of a winning team and help shape the future of finance with cutting-edge technology.
- Qualifications: Solid SQL skills and a passion for data analytics; eagerness to learn and grow.
The predicted salary is between 30000 - 40000 £ per year.
Lendable is on a mission to build the world's best technology to help people get credit and save money. We're building one of the world’s leading fintech companies and are off to a strong start. Among the fastest-growing tech companies in the UK, we’ve rebuilt the Big Three consumer finance products from scratch: loans, credit cards, and car finance. We’re growing fast, and there’s a lot more to do: we’re going after the two biggest Western markets (UK and US) where trillions worth of financial products are held by big banks with dated systems and painful processes.
We're looking for a Junior Analytics Engineer to join the analytical foundation for our US Cards team, the fastest-developing area of the business. In this role, you’ll work closely with analysts, product teams, backend engineers, and business stakeholders to help improve how data is structured, transformed, and consumed across the company. The role is fundamentally about contributing to a strong analytical foundation: helping teams move from question to insight quickly, while improving data quality, scalability, and maintainability.
You'll be supported by experienced engineers and given the space to grow — picking up new skills, deepening your SQL and dbt knowledge, and building confidence across a modern data stack.
- Contributing to the data models that support credit decisions, origination, portfolio analysis, and investor reporting.
- Building and improving dbt models and transformations, guided by senior engineers and in close collaboration with analysts and stakeholders.
- Acting as a bridge between analysts, backend engineers, product teams, and the data platform team to help ensure data is modelled and used effectively.
- Identifying opportunities to improve the efficiency, reliability, and cost-effectiveness of our transformation pipeline over time.
- Supporting the scaling of our data infrastructure as the business grows.
Our modern data stack: You’ll work with a modern analytics stack centred around SQL, Snowflake, dbt, Fivetran, and Claude. We're looking for someone with solid analytics engineering fundamentals - or the drive to develop them - and the curiosity to apply them in a fast-moving environment.
- Solid SQL skills and a willingness to keep improving them.
- A growing understanding of data modelling and how analytical datasets should be structured for reliability and usability.
- Comfort using AI tools to move faster and improve the quality of your work.
- Experience with Snowflake or another modern cloud data warehouse.
- An interest in learning from and eventually supporting analysts through shared patterns and good practices.
Flexible working: flexible approach tailored to each role. Hybrid roles require three days in-office weekly; fully remote roles include regular opportunities for in-person connection through socials and off-sites.
