Staff Analytics Engineer

Monzo; United States; Remote; USD 162,000 - 220,000; Full time

Benefits offered by this job

Relocation assistance

Visa sponsorship

Distributed UK working

Flexible working hours

Learning budget

Job summary

Monzo is seeking a Staff Analytics Engineer for Borrowing in the UK. You will architect and govern the data layer powering 1,700+ models across 12+ products, building scalable data products and reusable feature stores to support analytics, ML, decisioning, and regulatory reporting.

You will collaborate with backend engineers, product managers, and the data platform team to drive cross-product consistency, architecture patterns, and a high-performance data estate across geographies.

Qualifications

• You design data architectures that span multiple products or domains and scale coherently.
• You build governed, versioned data assets with clear ownership and SLAs.
• You apply analytics engineering systems at scale with modern tooling.

Responsibilities

• Architect Borrowing’s data layer at scale across 12+ products and 1,700+ models.
• Govern data products with contracts, ownership, and interfaces.
• Build reusable feature layers powering models, dashboards, and decisions.
• Scale analytics engineering infrastructure and improve developer experience.
• Drive cross-product data consistency and cross-geography alignment.
• Partner with backend, product, credit, and leadership on data strategy.

Skills

Data architecture

dbt at scale

BigQuery

CI/CD for data

Feature stores

Analytics engineering

Tools

dbt

BigQuery

Job description

Staff Analytics Engineer - Borrowing

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.

Location: London/Cardiff/UK Remote. Salary: £121,600-164,600 + Incentive Awards tied to your performance and benefits.

Our Mission in Borrowing

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.

Key Responsibilities

• 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.
• 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.

Who We’re Looking For

• 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 c