Staff Analytics Engineer

Were on a mission to make money work for everyone.

Were waving goodbye to the complicated and confusing ways of traditional banking.

After starting as a prepaid card our product offering has grown a lot in the last 10 years in the UK. As well aspersonal and business bank accounts we offer joint accounts accounts for 16-17 year olds a free kids account and credit cards in the UK with more exciting things to come beyond. Our UK customers can also save invest andcombine their pensions with us.

With our hot coral cards and get-paid-early feature combined with financial education on social media and our award winning customer service we have a long history of creating magical moments for our customers!

Were not about selling products - we want to solve problems and change lives through Monzo

Staff Analytics Engineer - Borrowing

London/Cardiff/UK Remote 00 stock and benefits Hear from the team

Our Borrowing Analytics Engineering Team

Our mission in Borrowing is to help people achieve their financial goals through better borrowing. Our customers borrow money to achieve something in their lives whether thats making a big life event affordable buying something they need now without affecting their monthly budget or getting by until payday. Were shaping this mission by building products our customers love while safely scaling some of Monzos biggest revenue lines.

Borrowing is one of Monzos most complex and fastest-growing domains. We operate 12 products across multiple geographies underpinned by 1700 data models and an analytics engineering team thats scaling to match. Were in the middle of a major data architecture transformation expanding into new markets and building the next generation of data infrastructure to support it all.

Were looking for a Staff Analytics Engineer to help shape how Borrowing builds and uses data at scale. Reporting to the Borrowing Data Director youll work across product credit engineering Data Platform and analytics engineering teams to turn complex technical problems into clearer systems stronger data products and better business decisions.

Youll play a key role by

• Architecting Borrowings data layer at scale. Partnering across Analytics Engineering Product Engineering Credit and Data Platform to shape how 1700 models across 12 products are structured connected and evolved. Youll set shared patterns that help teams build trusted consistent and scalable data products across Borrowing.
• Designing and governing data products. Moving us beyond ad-hoc tables toward well-defined contractual data assets with clear ownership SLAs documentation and interfaces. Youll work with teams across Borrowing and Data Platform to define what makes a Borrowing dataset production-grade and consumable by analytics ML decisioning and regulatory teams.
• Building feature stores and reusable analytical assets. Identifying cross-product signals (credit behaviour repayment patterns affordability risk indicators) that should be modelled once tested rigorously and consumed by many. Youll design the layer that turns raw product data into curated versioned features that power models dashboards and decisions.
• Scaling our analytics engineering infrastructure. Shaping the tooling patterns and developer experience that make an 80 person credit and data organisation more productive. This means influencing our data architecture and ways of working across data and credit disciplines while partnering with the central Data Platform team to ensure Borrowings needs are reflected in ingestion streaming and schema contract design.
• Driving cross-product data consistency. As we expand across geographies and product lines ensuring our data models are coherent and comparable. Youll work with AE leads and domain experts to define shared conventions and abstractions that allow us to reason about Borrowing as a whole not just product-by-product.
• Being a senior technical partner for Borrowings data estate. Partnering with backend engineers on source data payload design with product managers on measurement strategy with credit teams on decisioning data and with senior leadership on whats possible and whats next.
• Leading through influence and leverage. You wont manage people directly but youll shape how an entire domain builds data. Youll multiply the impact of AEs across Borrowing by setting the right patterns unblocking architectural decisions and raising the bar on what good looks like.

Wed love to hear from you if

• You think in systems not just queries. Youve designed data architectures that span multiple products or domains and you know how to keep them coherent as they scale. You can take ambiguous problems and turn them into a clear technical direction delivery sequence and set of trade-offs.
• Youve built data products not just data models. You understand the difference between a table that exists and a data asset thats governed documented versioned discoverable and trusted. Youve defined SLAs contracts interfaces or ownership models for data consumers and youre excited to do this at scale.
• You have deep fluency with analytics engineering systems and infrastructure. dbt at scale BigQuery or equivalent CI/CD for data testing frameworks and orchestration. You dont just use these tools you shape how teams use them. Youve hit the scaling limits and know what to do about them.
• You can design reusable feature layers. Youve designed contributed to or have a clear vision for reusable feature layers that serve multiple consumers including ML pipelines dashboards decisioning engines and regulatory reporting. You understand the trade-offs between freshness cost granularity correctness and ease of use.
• Youre comfortable at the platform boundary. You can have a productive conversation with a Data Platform engineer about ingestion patterns streaming vs. batch trade-offs schema evolution and infrastructure costs. You dont need to build the platform but you need to shape what it delivers.
• You connect technical choices to business outcomes. You care about whether data models feature layers and platform patterns actually improve decisions. You understand how product credit engineering and operational teams use data and you use that context to align people around better technical choices.
• You lead through others. You create leverage not by writing more SQL but by setting patterns reviewing designs unblocking teams and raising the standard. Youre energised by making 30 people more effective not by being the single expert.
• You communicate across altitudes. You can whiteboard a data architecture with a back-end engineer in the morning and present a strategic data roadmap to a director in the afternoon. You adapt your message to your audience without losing precision.
• You care about credit products. Youre excited or curious about the complexity of lending including risk affordability regulatory constraints and multi-product dynamics. You see it as a fascinating data domain not just a business vertical.

Interview process

Our typical process is structured as:

• Recruiter call
• Initial call
• 3 x 1 hours sessions (final interview)

Our average process takes around 3-4 weeks but we will always work around your availability.

Whats in it for you:

00 base

We can help you relocate to the UK

We can sponsor visas

This role can be based in our London office but were open to distributed working within the UK (with ad hoc meetings in London).

We offer flexible working hours and trust you to work enough hours to do your job well at times that suit you and your team.

Learning budget of 1000 a year for books training courses and conferences

And much more see our full list of benefits here

#LI-AS #LI-Remote

Equal opportunities for everyone

Diversity and inclusion are a priority for us and were making sure we have lots of support for all of our people to grow at Monzo. At Monzo were embracing diversity by fostering an inclusive environment for all people to do the best work of their lives with us. This is integral to our mission of making money work for everyone. You can read more in our blog 2026 Diversity and Inclusion Report and 2025 Gender Pay Gap Report.

Were an equal opportunity employer. All applicants will be considered for employment without attention to age ethnicity religion sex sexual orientation gender identity family or parental status national origin or veteran neurodiversity or disability status.

If you have a preferred name please use it to apply. We dont need full or birth names at application stage