Staff Analytics Engineer

Overview

In this role you shape Borrowing’s data at scale, turning complex data into trusted assets and enabling informed decisions across product, credit and analytics. You’ll define scalable data patterns, partner with multiple teams to productionize data assets, and drive a coherent data platform as the domain grows. You’ll lead architectural decisions and foster a culture of measurable impact, helping Monzo safely scale its borrowing business. This is a chance to influence data-driven decisions across geographies and products.

Pay / Benefits

• relocation to the UK
• visa sponsorship
• flexible working hours
• learning budget of 1,000 per year
• remote/hybrid working
• benefits package (full list available)

Responsibilities

• Architect Borrowing’s data layer at scale across 12+ products and 1,700+ models
• Design and govern data products with defined ownership, SLAs, and interfaces
• Build feature stores and reusable analytical assets powering models, dashboards, and decisions
• Scale analytics engineering infrastructure and improve developer experience
• Drive cross-product data consistency and shared conventions across Borrowing
• Serve as a senior technical partner for data estate, collaborating with backend, product, credit, and leadership
• Lead through influence, setting patterns and unblocking architectural decisions across the domain

Key requirements

• Systems thinking across multi-domain data architectures
• Experience turning data models into governed, versioned data assets with ownership and contracts
• Fluency with analytics engineering systems at scale (dbt, BigQuery or equivalent, CI/CD for data, testing, orchestration)
• Ability to design reusable feature layers serving ML, dashboards, decisioning, and regulatory reporting
• Comfort at the platform boundary, shaping ingestion, streaming vs. batch, and schema evolution
• Strong communication skills and ability to align product, credit, engineering, and leadership around technical choices
• Energetic about credit products and multi-product dynamics

• Collaborative cross-functional mindset
• Strong communication across levels (engineers to directors)
• Influence without formal authority
• dbt at scale
• BigQuery or equivalent
• CI/CD for data