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 Analytics Engineering 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 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 Wealth, Business Banking and Fincrime, 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 an 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 3 main stages:
- Initial Call
- Take home task
- Final Stage
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 firstname.lastname@example.org
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
Equal Opportunity Statement
We are actively creating an equitable environment for every Monzonaut to thrive.
Diversity and inclusion are a priority for us and we are making sure we have lots of support for all of our people to grow at Monzo. At Monzo, embracing diversity in all of its forms and 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 2022 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.
To apply for this job please visit boards.greenhouse.io.