Staff Analytics Engineer

Join Borrowing as a Staff Analytics Engineer, where you'll shape how we build and use data at scale. You'll work across various teams to architect our data layer, design and govern data products, build feature stores, scale our analytics engineering infrastructure, drive cross-product data consistency, and be a senior technical partner for our data estate. You'll have a significant impact on our data strategy and operations, and enjoy a range of benefits including flexible working hours, a learning budget, and generous parental leave.

• Architecting Borrowing’s data layer at scale, partnering across teams to shape how models are structured and evolved.
• Designing and governing data products, moving beyond ad-hoc tables toward well-defined, contractual data assets.
• Building feature stores and reusable analytical assets, identifying cross-product signals that should be modeled once and consumed by many.
• You think in systems, not just queries. You’ve designed data architectures that span multiple products or domains, and you know how to keep them coherent as they scale. You can take ambiguous problems and turn them into a clear technical direction, delivery sequence, and set of trade-offs
• You have deep fluency with analytics engineering systems and infrastructure. dbt at scale, BigQuery or equivalent, CI/CD for data, testing frameworks, and orchestration. You don’t just use these tools, you shape how teams use them. You’ve hit the scaling limits and know what to do about them
• You connect technical choices to business outcomes. You care about whether data models, feature layers, and platform patterns actually improve decisions. You understand how product, credit, engineering, and operational teams use data, and you use that context to align people around better technical choices
• You communicate across altitudes. You can whiteboard a data architecture with a back-end engineer in the morning and present a strategic data roadmap to a director in the afternoon. You adapt your message to your audience without losing precision
• You lead through others. You create leverage not by writing more SQL, but by setting patterns, reviewing designs, unblocking teams, and raising the standard. You’re energised by making 30+ people more effective, not by being the single expert
• You care about credit products. You’re excited, or curious, about the complexity of lending, including risk, affordability, regulatory constraints, and multi-product dynamics. You see it as a fascinating data domain, not just a business vertical
• You’ve built data products, not just data models. You understand the difference between a table that exists and a data asset that’s governed, documented, versioned, discoverable, and trusted. You’ve defined SLAs, contracts, interfaces, or ownership models for data consumers, and you’re excited to do this at scale
• You’re comfortable at the platform boundary. You can have a productive conversation with a Data Platform engineer about ingestion patterns, streaming vs. batch trade-offs, schema evolution, and infrastructure costs. You don’t need to build the platform, but you need to shape what it delivers
• You can design reusable feature layers. You’ve designed, contributed to, or have a clear vision for reusable feature layers that serve multiple consumers, including ML pipelines, dashboards, decisioning engines, and regulatory reporting. You understand the trade-offs between freshness, cost, granularity, correctness, and ease of use