Monzo
Staff Analytics Engineer
Remote role where the employee must remain based in a particular country.
United Kingdom only
Employer listed it 9 days ago ¡ Added 5 days ago
First listed 9 days ago and still open.
Salary
ÂŁ121,600 to ÂŁ164,600
Location
United Kingdom only
Timezone
GMT
Contract
Full-time
Experience
Lead
Category
Data
Stated by the employer in the job description
Remote flexibility
Work from home
This is a remote role, but the employee must be based in United Kingdom. It is work from home rather than work from anywhere.
What the employer says
- Source listing states candidate location: "Cardiff, London or Remote (UK), UK"
- Job description states: "based in our London office"
What Nomaders makes of it
- Payroll and tax are likely handled in that country only
The quotes above are the employer's own words; the reading is ours. Always check the original listing and employment terms before working from another country.
About the role
đ Weâre on a mission to make money work for everyone.
Weâre 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!
Weâre not about selling products - we want to solve problems and change lives through Monzo â¤ď¸
Staff Analytics Engineer - Borrowing
đLondon/Cardiff/UK Remote | đ° ÂŁ121,600-164,600 + Incentive Awards tied to your performance and benefits | Hear from the team â¨
â 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 â whether thatâs making a big life event affordable, buying something they need now without affecting their monthly budget, or getting by until payday. Weâre shaping this mission by building products our customers love, while safely scaling some of Monzoâs biggest revenue lines.
Borrowing is one of Monzoâs most complex and fastest-growing domains. We operate 12+ products across multiple geographies, underpinned by 1,700+ data models and an analytics engineering team thatâs scaling to match. Weâre 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.
Weâre looking for a Staff Analytics Engineer to help shape how Borrowing builds and uses data at scale. Reporting to the Borrowing Data Director, youâll 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.
đ Youâll play a key role byâŚ
Architecting Borrowingâs 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. Youâll 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. Youâll work with teams across Borrowing and Data Platform to define what makes a Borrowing dataset âproduction-gradeâ 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. Youâll 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 Borrowingâs 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. Youâll 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 Borrowingâs 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 whatâs possible and whatâs next.
Leading through influence and leverage. You wonât manage people directly, but youâll shape how an entire domain builds data. Youâll multiply the impact of AEs across Borrowing by setting the right patterns, unblocking architectural decisions, and raising the bar on what good looks like.
𤊠Weâd love to hear from you ifâŚ
You think in systems, not just queries. Youâve 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.
Youâve built data products, not just data models. You understand the difference between a table that exists and a data asset thatâs governed, documented, versioned, discoverable, and trusted. Youâve defined SLAs, contracts, interfaces, or ownership models for data consumers, and youâre 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 donât just use these tools, you shape how teams use them. Youâve hit the scaling limits and know what to do about them.
You can design reusable feature layers. Youâve 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.
Requirements
The employer hasn't listed requirements separately, they're described in the role summary above and on the original listing.
Benefits
- ¡âď¸ We can help you relocate to the UK
- ¡â We can sponsor visas
- ¡đThis role can be based in our London office, but we're open to distributed working within the UK (with ad hoc meetings in London).
- ¡ⰠWe offer flexible working hours and trust you to work enough hours to do your job well, at times that suit you and your team.
- ¡đ Learning budget of ÂŁ1,000 a year for books, training courses and conferences
How to apply
- 1Check the flexibility label above, work from home, matches where you plan to live and work.
- 2Tailor your CV to the role at Monzo, mentioning your remote working experience and working hours (GMT).
- 3Apply directly on the employer's careers page using the button below. Nomaders never handles your application.
Found 5d ago. Last checked today. Always confirm the details on the original posting, salary and location can change after publication.
Listing sourced from Company boards.
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