Analytics Engineer

Free resume; Cardiff; Hybrid; GBP 60,000 - 90,000; Full time

Benefits offered by this job

Learning budget

Macbooks provided

Flexible hours

Remote work setup support

Job summary

Monzo is seeking an Analytics Engineer to join our Analytics Engineering team. You’ll help build downstream data models and optimise our BI platform, Looker, to support decision making and financial reconciliation.

You’ll work in a multi-disciplinary squad, loading and transforming data (primarily BigQuery), reducing cloud costs and applying our best practices to maintain high data quality. This role offers flexibility within the UK (including Cardiff) and a learning budget, with an emphasis on

Qualifications

• Experience with Data Modelling, ETL, and Big Data engineering or analysis.
• Strong SQL skills and data modelling experience.
• Interest in Data Warehousing concepts and attention to detail.

Responsibilities

• Support building robust pipelines and data models downstream of backend services (BigQuery).
• Optimize Data Warehouse to reduce complexity and cost.
• Define and manage best practices for Data Warehouse design and testing.
• Follow established team standards and collaborate with other disciplines.
• Monitor and improve data quality in the warehouse.

Skills

SQL

Data modelling

ETL

Big data

Looker

Tools

BigQuery

Looker

Job description

Job Description

We’re on a mission to make money work for everyone.

We’re waving goodbye to the complicated and confusing ways of traditional banking.

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

Our Analytics Engineering discipline works in the intersection between data, engineering and our collectives - Money, Borrowing, Operations and Financial Crime and beyond. The 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 be an individual contributor in our Analytics Engineering team, working across a variety of projects to spot patterns in the way we build our Data Warehouse and optimise our BI platform, Looker. You’ll help us load and transform even more data, minimise our cloud costs, contribute using our best practices, keeping quality high.

We are at an exciting stage in our growth and have roles available across Growth and Finance, so do let us know if you’re interested in a specific area.

What you’ll be working on

Working in a multi-disciplinary data / engineering squad, you will:

• Support the building of robust pipelines and data models downstream of backend services (mostly in BigQuery) that support internal reporting, machine learning as well as financial and regulatory use cases.
• Build with optimisation of our Data Warehouse in mind, spotting and raising 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.
• Follow our established best practices and standards defined by the team.
• Investigate and effectively work with colleagues from other disciplines to monitor and improve data quality within the warehouse.

You should apply if:

• You have some experience and a passion for Data Modelling, ETL projects and Big Data as an engineer, developer or analyst.
• You are confident with SQL and data modelling.
• You are comfortable with general Data Warehousing concepts.
• You have an eye for detail.
• You’re ready to be part of a growing team in new areas of growth!

The interview process:

Our interview process involves 4 main stages:

• Recruiter Call (30 mins)
• Initial Call with Hiring Manager (45 mins)
• Take home task
• Final Loop consisting of x2 hour long interviews to assess a Case Study and Behavioural

This process should take around 3-4 weeks - your schedule is really important to us, so we promise to be as flexible as possible!

We have some guidelines on using Artificial Intelligence (AI) to ace an application and interview at Monzo. You can read them here.

We’ll only close this role once we have enough applications for the next stage. Please submit your application as soon as possible to make sure you don’t miss out.

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).

• £1,000 learning budget each year to use on books, training courses and conferences.
• We will set you up to work from home; all employees are given Macbooks and for fully remote workers we will provide extra support for your work-from-home setup.
• We offer flexible working hours and trust you to work enough hours to do your job well, and at times that suit you and your team.

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.