|Hours||37.5 - 37.5 Hours|
We’re here to make money work for everyone and we're doing things differently. For too long, banking has been obtuse, complex and opaque.
We want to change that and build a bank with everyone, for everyone. Our amazing community suggests features, test the app and give us constant feedback so we can build something everyone loves.
We're focused on solving problems, rather than selling financial products. We want to make the world a better place and change people's lives through Monzo.
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. You’ll help us minimise our cloud costs, drive best practices across all of our Data Discipline and scale and automate our data governance.
Enable Monzo to Make Better Decisions, Faster
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 – 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 you’ll be working on:
Working in a multi-disciplinary data / engineering squad, you will:
You should apply if:
Nice to haves:
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@example.com
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
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.