At a Glance
- Tasks: Lead data architecture and enhance analytics for innovative borrowing solutions.
- Company: Join a forward-thinking bank shaping the future of finance.
- Benefits: Competitive salary, flexible hours, learning budget, and relocation support.
- Other info: Dynamic remote work culture with excellent career growth opportunities.
- Why this job: Make a real impact on financial goals through data-driven decision making.
- Qualifications: Passion for data modelling, SQL expertise, and experience in cross-functional teams.
📍London, Cardiff or Remote in the UK | 💰 £97,800 -125,000 + Benefits
Our Borrowing Analytics Engineering Team:
Our Mission in Borrowing is to enable people's financial goals through better borrowing. Our customers look to borrow money to enable them to achieve something in their lives - whether that’s making a big life event affordable, buying something they need now without affecting their monthly budget, or getting by until payday. And we’re looking to shape this mission by building products that our customers love, whilst scaling those top revenue lines across the business safely.
We're looking for a Lead Analytics Engineer within our borrowing team to help build world class service for the bank of the future. You will play a critical role in overseeing our foundational data platforms, identifying and driving opportunities to enhance our current capabilities. Your expertise will be pivotal in allowing us to scale into new global markets, build new products and shape the future of how we serve our customers. We have a strong culture of data-driven decision making across the whole company. And we're great believers in powerful, real-time analytics and empowerment of the wider business.
You’ll play a key role by...
- Serving as a data architect for Monzo’s Borrowing data, contributing to the design and scalability of data models that measure the performance of our product suite.
- Develop robust data models downstream of backend services, primarily in BigQuery, to support internal reporting, machine learning, large language models, as well as financial and regulatory use cases.
- Be a key voice in shaping and maintaining best practices for our Data Warehouse, including source data payload design, logical data modelling, implementation, metadata, and testing standards.
- Collaboratively set standards and work with data across Monzo, fostering knowledge sharing and continuously improving data practices.
- Contribute to prioritising data governance issues, ensuring a comprehensive approach to data integrity and compliance.
- Being a key technical leader who’s able to champion central platform initiatives that aim to elevate the data standards across Borrowing and beyond.
We’d love to hear from you:
- You have a strong passion for data modelling, ETL projects, and Big Data.
- You enjoy working with data streams from various services, such as financial, transactional, and operational systems.
- SQL and data modelling are second nature to you, and you are comfortable with general Data Warehousing concepts.
- You are committed to continuous improvement, proactively identifying opportunities and addressing challenges in your work and the work of others.
- You have experience building robust and reliable data sets that require a high level of control.
- You enjoy working with cross functional fast moving teams and are passionate about serving our customers.
- You are able to think strategically about credit products and how our underlying data models will unlock more insights for our team and more value for our customers.
- You are excited about enabling other data scientists, analytics engineers and credit analysts by sharing your expertise on data architecture.
- You have the ability to shape big, ambiguous data domains and get the required buy-in from key leaders across the business.
- You are able to shape and manage the technical roadmap of an entire domain and execute against the project plan’s deliverables.
- You are leading through the contributions of others by effectively leveraging the multiplier effect to create exponential value across Borrowing and Analytics Engineering.
- Excel in cross-functional stakeholder communication (back-end engineers, product managers, and credit analysts), while also effectively engaging with senior technical leaders.
The interview process:
Our interview process involves 4 main stages: Recruiter call, Initial call, Technical task, 3 x 1 hours sessions (final interview). Our average process takes around 3-4 weeks but we will always work around your availability.
What’s in it for you:
- 💰 £97,800-£125,000 base + Benefits
- ✈️ 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
Remote Lead Analytics Engineer, Borrowing in Plymouth employer: Referrals Only
At Monzo, we pride ourselves on being an exceptional employer that champions a culture of data-driven decision making and innovation. As a Lead Analytics Engineer in our Borrowing team, you'll enjoy flexible working arrangements, a generous learning budget, and the opportunity to shape the future of financial services while collaborating with passionate professionals. Our commitment to employee growth and empowerment ensures that you will thrive in a supportive environment that values your contributions and fosters continuous improvement.
StudySmarter Expert Advice🤫
We think this is how you could land Remote Lead Analytics Engineer, Borrowing in Plymouth
✨Tip Number 1
Network like a pro! Reach out to current employees on LinkedIn or other platforms. Ask them about their experiences and any tips they might have for the interview process. This insider info can give us a leg up!
✨Tip Number 2
Prepare for those technical tasks! Brush up on your SQL and data modelling skills, as these will likely come up in the interviews. We want to show that we can handle the data challenges head-on!
✨Tip Number 3
Practice makes perfect! Set up mock interviews with friends or use online platforms to simulate the interview experience. This will help us feel more confident and articulate our thoughts clearly.
✨Tip Number 4
Don’t forget to showcase our passion for data! During the interviews, share examples of how we've used data to drive decisions or improve processes. Let’s make it clear that we’re not just about numbers, but about making a real impact!
We think you need these skills to ace Remote Lead Analytics Engineer, Borrowing in Plymouth
Some tips for your application 🫡
Tailor Your Application:Make sure to customise your CV and cover letter for the Lead Analytics Engineer role. Highlight your experience with data modelling, ETL projects, and any relevant Big Data skills. We want to see how your background aligns with our mission in Borrowing!
Show Your Passion for Data:Let your enthusiasm for data shine through! Share specific examples of how you've tackled challenges in data architecture or analytics. We love candidates who are proactive and committed to continuous improvement, so don’t hold back!
Be Clear and Concise:When writing your application, keep it clear and to the point. Use bullet points where possible to make your achievements stand out. We appreciate straightforward communication, especially when it comes to complex topics like data!
Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it shows you’re keen on joining our team at StudySmarter!
How to prepare for a job interview at Referrals Only
✨Know Your Data Inside Out
As a Lead Analytics Engineer, you'll need to demonstrate your deep understanding of data modelling and ETL processes. Brush up on your SQL skills and be ready to discuss specific projects where you've built robust data models or tackled complex data challenges.
✨Showcase Your Strategic Thinking
This role requires you to think strategically about credit products and data insights. Prepare examples of how you've shaped data architecture in previous roles and how it led to improved decision-making or product development.
✨Communicate Like a Pro
You'll be working with cross-functional teams, so practice articulating your ideas clearly. Be ready to explain technical concepts in a way that non-technical stakeholders can understand, showcasing your ability to bridge the gap between data and business needs.
✨Prepare for Technical Challenges
Expect technical tasks during the interview process. Familiarise yourself with BigQuery and data warehousing concepts. Consider doing mock interviews or coding challenges to sharpen your problem-solving skills and get comfortable with the types of questions you might face.
