Analytics Engineering Manager — Lead Data, Scale & Governance
Referrals Only About the role
Overview
We will lead and nurture a team of 5 to 6 analytics engineers through coaching, support, regular 1:1s, and continuous feedback.
We will work as a hands‑on leader, building a discipline of exceptional analytics engineers and raising the standard of data at Monzo.
The role involves prioritising initiatives and projects, working closely with other leads across our collectives, participating in reviews, architecture and design leadership, and developing our own pipeline changes.
We will contribute to hiring within Analytics Engineering and work with other leads to deliver scalable, consistent governance and best practices.
We are Monzo, and our Core Banking mission is to make everyday money work for everyone.
Our Core Analytics Engineering team supports the current account used by over 12million users and builds day‑to‑day money management features such as Trends, Salary Sorter, Bills Pots, Joint Accounts, Under16 accounts, and Subscriptions.
We are growing toward 20million customers and work at the intersection of data, engineering, and our collectives across Core, Money, Borrowing, Operations, Financial Crime, and beyond.
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Your tasks
Lead and nurture a team of analytics engineers while driving data initiatives.
Your profile
Experience in analytics engineering and strong leadership abilities.
What's also included
Enjoy competitive pay, flexible working, and opportunities for professional growth.
Tech stack & ways of working
Analytics Engineering Manager — Lead Data, Scale & Governance employer: Referrals Only
As a Remote Senior Lead Product Designer at our innovative company, you'll be part of a dynamic design team dedicated to creating impactful solutions that make money work for everyone. We foster a collaborative and inclusive work culture, offering extensive employee growth opportunities and a competitive benefits package, all while allowing you the flexibility of remote work from anywhere in the UK. Join us to contribute to meaningful projects and experience a supportive environment that values creativity and professional development.
Your perspectives
Make a real impact on financial tools used by millions while developing your leadership skills.
StudySmarter Expert Advice
Get Involved in Data Science Meetups
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Show Off Your Projects
Start building a public portfolio showcasing your data science projects on platforms like GitHub or personal websites. Highlight unique analyses or models you've developed. This not only demonstrates your skills but also gets your name out there for roles like Analytics Engineering Manager — Lead Data, Scale & Governance at Referrals Only.
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Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like Referrals Only.
Apply Directly through Our Website
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Some tips for your application 🫡
Show Off Your Projects
In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
Quantify Your Achievements
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Craft a Tailored Cover Letter
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Stand Out with Relevant Courses and Certifications
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How to prepare for a job interview at Referrals Only
Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
Showcase Your Projects
Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
Get Comfortable with Python and R
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Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
