Scan your resume against ATS criteria for this Staff Analytics Engineer role at Monzo.
We’re 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 as https://monzo.com/current-account/personal personal and https://monzo.com/business-banking business bank accounts, we offer https://monzo.com/current-account/joint-account joint accounts, https://monzo.com/current-account/16-17 accounts for 16-17 year olds, a https://monzo.com/current-account/under-16s free kids account and https://monzo.com/flex credit cards in the UK, with more exciting things to come beyond. Our UK customers can also https://monzo.com/savings save, https://monzo.com/investments invest and https://monzo.com/pensions combine 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!
We’re not about selling products - we want to solve problems and change lives through Monzo ❤️
📍London/Cardiff/UK Remote | 💰 £121,600-164,600 + Incentive Awards tied to your performance andhttps://monzo.com/careers/ benefits |https://www.youtube.com/watch?v=U62l09nB0M4 Hear from the 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 that’s making a big life event affordable, buying something they need now without affecting their monthly budget, or getting by until payday. We’re shaping this mission by building products our customers love, while safely scaling some of Monzo’s biggest revenue lines.
Borrowing is of Monzo’s most complex and fastest-growing domains. We operate 12+ products across multiple geographies, underpinned by 1,700+ data models and an analytics engineering team that’s scaling to match. We’re 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.
We’re looking for a Staff Analytics Engineer to help shape how Borrowing builds and uses data at scale. Reporting to the Borrowing Data Director, you’ll 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.
Partnering across Analytics Engineering, Product, Engineering, Credit, and Data Platform to shape how 1,700+ models across 12+ products are structured, connected, and evolved. You’ll set shared patterns that help teams build trusted, consistent, and scalable data products across Borrowing.
. Moving us beyond ad-hoc tables toward well-defined, contractual data assets with clear ownership, SLAs, documentation, and interfaces. You’ll 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.
. Identifying cross-product signals (credit behaviour, repayment patterns, affordability, risk indicators) that should be modelled, tested rigorously, and consumed by many. You’ll design the layer that turns raw product data into curated, versioned features that power models, dashboards, and decisions.
. 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 Borrowing’s needs are reflected in ingestion, streaming, and schema contract design.
. As we expand across geographies and product lines, ensuring our data models are coherent and comparable. You’ll 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.
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 what’s possible and what’s next.
You won’t manage people directly, but you’ll shape how an entire domain builds data. You’ll multiply the impact of AEs across Borrowing by setting the right patterns, unblocking architectural decisions, and raising the bar on what good looks like.
You’ve 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.
You understand the difference between a table that exists and a data asset that’s governed, documented, versioned, discoverable, and trusted. You’ve defined SLAs, contracts, interfaces, or ownership models for data consumers, and you’re excited to do this at scale.
dbt at scale, BigQuery or equivalent, CI/CD for data, testing frameworks, and orchestration. You don’t just use these tools, you shape how teams use them. You’ve hit the scaling limits and know what to do about them.
You’ve 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.
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 don’t need to build the platform, but you need to shape what it delivers.
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 create leverage not by writing more SQL, but by setting patterns, reviewing designs, unblocking teams, and raising the standard. You’re energised by making 30+ people more effective, not by being the single expert.
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’re 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.
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.
💰 £121,600-164,600 + Incentive Awards tied to your performance andhttps://monzo.com/careers/ benefits
✈️ We can help you relocate to the UK
✅ We can sponsor visas
📍This role can be based in our London office, but we're 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 £1,000 a year for books, training courses and conferences
➕ And much more, see our full list of benefitshttps://monzo.com/careers/
#LI-AS #LI-Remote
Diversity and inclusion are a priority for us and we’re making sure we have lots of support for all of our people to grow at Monzo. At Monzo, we’re 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 https://monzo.com/blog/diversity-and-inclusion blog, 2026 https://monzo.com/blog/our-2026-diversity-and-inclusion-report Diversity and Inclusion Report and 2025 https://monzo.com/blog/gender-pay-gap-report-2025 Gender Pay Gap Report.
We’re 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 don't need full or birth names at application stage 😊
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.
How to apply for Staff Analytics Engineer at Monzo?
Click the "Apply on Company Website" button on this page to submit your application directly on the employer's official portal.
What is the salary for this role?
The salary for this role is £121,600-164,600 per annum.
What experience is required?
10+ years of experience is required.
Is this position still open?
Yes, currently active and accepting applications.
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