Going rate for this occupation: £34,900 · UK median pay £38,572
Home Office going rates from
Where this salary sits
UK pay for this occupation
This role£121,600stated · above the range ONS published
Going rate£34,900
UK median£38,572
ONS Annual Survey of Hours and Earnings 2025, full-time gross annual pay, UK. ONS published no separate row for this region and occupation, so the national curve is shown.View these figures as a table
ASHE pay percentiles for Data analysts in UK
Percentile
Pay
10th
£27,338
25th
£30,835
50th
£38,572
75th
£47,045
Going rate
£34,900
UK median
£38,572
Sponsorship
Sponsorship chance
Moderate
·The advert offers sponsorship
·Licensed for Skilled Worker
·Salary clears the going rate
On the public records we hold, sponsorship for this role looks possible: the advert offers sponsorship, and licensed for Skilled Worker.
Confidence: high
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Why
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We read this advert for what it asks, check each line against your CV and show you the evidence for every judgement.
🚀 We’re on a mission to make money work for everyone.
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 personal 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 and 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 ❤️
Staff Analytics Engineer - Borrowing
📍London/Cardiff/UK Remote | 💰 £121,600-164,600 + Incentive Awards tied to your performance 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 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 one 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.
🔑 You’ll play a key role by…
Architecting Borrowing’s data layer at scale. 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.
Information from public records, not immigration advice.
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Routes and ratings on this sponsor's licence
Route
Rating
Status
Global Business Mobility: Senior or Specialist Worker
Worker (A rating)
Current
Skilled Worker
Worker (A rating)
Current
Going-rate check
Occupation code 3544 is not eligible for the Skilled Worker route on the current rules.
Information from public records, not immigration advice.
Designing and governing data products . 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.
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. You’ll 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 Borrowing’s 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. 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.
Being a senior technical partner for Borrowing’s 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 what’s possible and what’s next.
Leading through influence and leverage. 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.
🤩 We’d love to hear from you if…
You think in systems, not just queries. 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’ve built data products, not just data models. 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.
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 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 can design reusable feature layers. 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’re 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 don’t 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. You’re 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. 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.
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.
What’s in it for you:
💰 £121,600-164,600 + Incentive Awards tied to your performance and 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 benefits
here
#LI-AS #LI-Remote
Equal opportunities for everyone
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 blog , 2026 Diversity and Inclusion Report and 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 😊
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