Lead Analytics Engineer Borrowing
AI Summary
A Lead Analytics Engineer shaping borrowing analytics at Monzo, owning foundational data platforms, designing scalable data models in BigQuery, and guiding best practices for the data warehouse to support reporting, ML, and regulatory needs.
About this role
Lead Analytics Engineer Borrowing
Company: Monzo Location: Cardiff, London Type: Remote Category: design, architect, support, testing, voice, financial, bank, lead, analytics, engineer, engineering,
đLondon, Cardiff or Remote in the UK | đ° ÂŁ97,800 -125,000 + Benefits | Hear from the team âš
âOur 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.
đYou'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.
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