高级分析工程师

🚀 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 ❤️

📍London/Cardiff/UK Remote | 💰 £76,500-£95,000 ➕ Incentive Awards tied to your performance and Benefits | Hear from the team ✨

Analytics Engineering at Monzo We have around 60 Analytics Engineers out of roughly 300 data practitioners in total - and we have big ambitions for the discipline. Analytics Engineering is at the core of how we build our data to enable Monzo to make better and faster decisions by having a performant, scalable and high quality data warehouse. As an Analytics Engineer here you'll be working collaboratively with other disciplines like product, engineering and data science, and we run regular knowledge-sharing sessions so you’ll learn loads about everything from our data modelling principles to how banks work and effective communication.

What you’ll be working on:

The Analytics Engineering team is responsible for building downstream data models from backend services with the desire to make our Data Warehouse a genuine competitive advantage for Monzo. We want a discipline capable of building an amazing Data Warehouse to support decision making, Business Intelligence, key financial reconciliation processes and best in class analytics and Data Science.

You’ll enable our data driven approach, and:

• Support the building of robust data models downstream of backend services (mostly in BigQuery) that support internal reporting, machine learning as well as financial and regulatory use cases.

• Focus on optimisation of our Data Warehouse, spotting opportunities to reduce complexity and cost.

• Help define and manage best practices for our Data Warehouse. This may include payload design of source data, logical data modelling, implementation, metadata and testing standards.

• Set standards and ways of working with data across Monzo, working collaboratively with others to make it happen.

• Take established best practices and standards defined by the team, applying them within other areas of the business.

• Investigate and effectively work with colleagues from other disciplines to monitor and improve data quality within the warehouse.

• Contribute to prioritisation of data governance issues

• We all own and support the pipelines we contribute to, and on call support out of hours will be expected from time to time as part of this role

We’d love to hear from you if…

• You enjoy working with cross functional fast moving teams and are passionate about serving small businesses.

• You are able to think strategically about the Business Banking product and how our underlying data models will unlock more insights for our team and more value for our customers.

• You have a strong passion for data modelling, ETL projects, and Big Data.

• You enjoy working with data streams from various services, such as financial, transactional, and operational systems.

• SQL and data modelling are second nature to you, and you are comfortable with general Data Warehousing concepts.

• You are committed to continuous improvement, proactively identifying opportunities and addressing challenges in your work and the work of others.

Nice to haves

• Any experience working within a finance function or knowledge of accounting.

• Experience working in a highly regulated environment (e.g. finance, gaming, food, health care).

• Knowledge of regulatory reporting and treasury operations in retail banking

• Exposure to Python, Go or similar languages.

• Have previously used dbt, dataform or similar tooling.

• Used to AGILE ways of working (Kanban, Scrum)

The Interview Process:

Our interview process involves 3 main stages:

• 30 minute recruiter call

• 45 minute call with the hiring manager

• Take home task

• 2-part final stage

Our average process takes around 3 weeks but we will always work around your availability.Please also use that email to let us know if there's anything we can do to make your application process easier for you, because of disability, neurodiversity or any other personal reason.

What’s in it for you:

✈️ 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-AS1 #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 😊