At a Glance
- Tasks: Lead a team of analytics engineers to enhance data-driven decision making.
- Company: Join Monzo, a revolutionary fintech company changing banking for everyone.
- Benefits: Competitive salary, flexible working hours, and a £1,000 learning budget.
- Other info: Diverse and inclusive workplace with excellent career growth opportunities.
- Why this job: Make a real impact in a dynamic environment while shaping the future of finance.
- Qualifications: Experience in managing engineers and strong data warehousing skills.
The predicted salary is between 97800 - 120000 £ per year.
We're on a mission to make money work for everyone. We're waving goodbye to the complicated and confusing ways of traditional banking. After starting as a prepaid card, our product offering has grown a lot in the last 10 years in the UK. As well as personal and business bank accounts, we offer joint accounts, accounts for 16-17 year olds, a free kids account and credit cards in the UK, with more exciting things to come beyond. Our UK customers can also save, invest and combine their pensions with us. 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 goal in Growth and Marketing is to build Monzo into a global brand people love. We're the team that finds exciting new ways to bring customers to Monzo and keep them engaged once they join. We create the features and cool stuff that gets everyone talking about us. We also figure out the best ways to chat to our customers – what products to talk about and when to reach out. Data is super important in everything we do, and this role will lead the team making sure our Growth and Marketing folks can easily use data to inform their everyday decisions.
Our Analytics Engineering discipline works in the intersection between data, engineering and our collectives - Money, Borrowing, Operations and Financial Crime and beyond. The AE teams are 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 a reliable and scalable Data Warehouse to support decision making in a cost-effective and performant manner.
Managers within Data have two primary responsibilities; people and technical products. Your focus will be on helping engineers with their personal and professional development, listening and guiding them through hard times and celebrating their successes. You will also be leading and participating directly in technical initiatives and helping Monzo shape its Data organisation, ensuring the team focuses on valuable work, shipping things with a level of care and attention to detail. There will be a strong focus on delivering best practice across all of our data discipline and helping bring a new level of maturity around Data Governance principles, working in collaboration with others to deliver this.
Working in a multi-disciplinary team, you will:
- Be a hands-on leader in building a discipline of exceptional analytics engineers working to make Data at Monzo the gold standard within the industry.
- Nurture between 3 to 4 engineers, supporting, coaching and developing high performing engineers through regular 1:1s, continuous feedback and relationships with others.
- Aid prioritisation of initiatives and projects, working closely with other leads for each of our Monzo collectives.
- Be hands-on through participating in the review cycle, architecture and design leadership and development of your own changes to the pipelines.
- Be part of the hiring team within Analytics Engineering.
- Work closely with other leads to deliver a scalable, consistent approach to governance and best practices.
- Drive effective project management of central Analytics Engineering projects, ensuring they're well scoped and delivered to deadlines.
- Establish yourself as a trusted partner to various collectives and the leadership team, with the capacity for getting things done, be it either hands-on or by leading others.
We all own and support the pipelines we contribute to, and on-call support out of hours will be expected from time to time as part of this role.
We'd love to hear from you if...
- You have experience managing or mentoring the performance and development of high-performing engineers.
- You have strong experience in data warehousing architecture at scale.
- You have experience and a passion for leading data warehousing, data visualisation, big data or ETL projects as an analyst, developer, designer or architect.
- You know what it takes to hire great engineers within the data space.
- You're equally comfortable working hands-on and leading a team.
Nice To Haves:
- Any experience working within a finance or banking environment.
- Experience working in a highly regulated environment (e.g. finance, insurance, gaming, food, health care).
- Experience with any of our stack of dbt, BigQuery and Looker.
Not ticking every box? That's totally okay! Studies show that women and people of colour might hesitate to apply unless they meet every single requirement. At Monzo, we're dedicated to creating a diverse and welcoming team. If you're passionate about this role and keen to learn and grow with us, we encourage you to apply— even if you don't have everything that's listed just yet. Drop us your application, we'd love to hear from you!
What's in it for you:
- £97,800 - £120,000.
- We'll help you relocate to the UK.
- We can sponsor your visa.
- 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, and at times that suit you and your team.
- £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.
- Plus lots more! Read our full list of benefits.
The application journey has 4 key steps:
- Recruiter Screening Call.
- Initial Call.
- Take Home Task.
- Final Loop (3 sessions - case study, collaboration and people leadership).
This process should take around 2-3 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.
You'll hear from us throughout the application process, but if you've got any questions, please reach out to tech-hiring@monzo.com. You can also use this email address to let us know if there's anything we can do to make the process easier for you because of disability, neurodiversity or anything else.
For more insight into the AE team at Monzo, check out our podcast with John Azzopardi one of our Senior Leaders in AE.
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, 2023 Diversity and Inclusion Report and 2024 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.
If you have a preferred name, please use it to apply. We don't need full or birth names at application stage.
StudySmarter Expert Advice🤫
We think this is how you could land Remote Analytics Engineering Manager, Growth & Marketing in Chester
✨Get Involved in Data Science Meetups
Tap into local data science meetups or workshops to connect with fellow enthusiasts and professionals. These events are goldmines for networking, and sometimes even lead directly to job openings at companies like Grabjobs!
✨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 Remote Analytics Engineering Manager, Growth & Marketing at Grabjobs.
✨Leverage Professional Networks
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 Grabjobs.
✨Apply Directly through Our Website
When you find a suitable opening like Remote Analytics Engineering Manager, Growth & Marketing at Grabjobs, make sure to apply directly through our website. It gives you an edge and shows you're keen to join our team. Plus, who doesn’t love a direct application? It’s easier than navigating through job boards!
We think you need these skills to ace Remote Analytics Engineering Manager, Growth & Marketing in Chester
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:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!
Craft a Tailored Cover Letter:For a full-time role at Grabjobs, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Grabjobs. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at Grabjobs
✨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
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at Grabjobs!
✨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.