đ Weâre on a mission to make money work for everyone.
Weâre 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!
Weâre not about selling products - we want to solve problems and change lives through Monzo â¤ď¸
Hear from our team about what it's like working at Monzo â¨
About our Team:
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 a senior 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. Youâll help us minimise our cloud costs, drive best practices across all of our Data Discipline and scale and automate our data governance.
At the core of this mission sits our data platform. We're great believers in powerful, real-time analytics and empowerment of the wider business. Every engineer at Monzo is responsible for collection of relevant analytics events from their microservices. We optimise for simplicity and re-usability â all our data lives in one place and is made available via our data warehouse in Google BigQuery. 90% of day-to-day data-driven decisions are covered by self-serve analytics through Looker which gives data scientists the head space to focus on more impactful business questions and analyses.
What youâll be working on:
Working in a multi-disciplinary data / engineering squad, you will:
The Interview Process:
Our interview process involves 3 main stages:
Our average process takes around 2-3 weeks but we will always work around your availability. You will have the chance to speak to our recruitment team at various points during your process but if you do have any specific questions ahead of this please contact us on [email protected] 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.
Whatâs in it for you:
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).
â° 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.
đLearning budget of ÂŁ1,000 a year for books, training courses and conferences
âAnd much more, see our full list of benefits here
If you prefer to work part-time, we'll make this happen whenever we can - whether this is to help you meet other commitments or strike a great work-life balance.
#LI-SL1 #LI-REMOTE
Equal opportunities for everyone
Diversity and inclusion are a priority for us and weâre making sure we have lots of support for all of our people to grow at Monzo. At Monzo, weâre 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, 2022 Diversity and Inclusion Report and 2023 Gender Pay Gap Report.
Weâre 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.
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