Staff Analytics Engineer

About the role

Monzo is seeking a Staff Analytics Engineer to join its Borrowing division. This role is in shaping and scaling the data infrastructure that underpins Monzo's lending products. You will be responsible for ensuring the quality, accessibility, and reliability of data used across multiple teams and functions. Your work will involve transforming complex data challenges into , scalable systems that facilitate decision-making, product development, and strategic initiatives. As a senior member of the analytics engineering team, you will collaborate closely with data engineers, product managers, credit teams, and other stakeholders to establish best practices and architectural standards. This position offers an to influence how data supports Monzo's growth in the lending space, contributing to innovative solutions that impact millions of customers.

Key facts

What you'll do

• Lead the design and management of the data architecture for Monzo's Borrowing domain, overseeing a large and complex data environment with over 1,700 data models across more than 12 products. Your work will ensure that data systems are scalable, reliable, and aligned with business needs.
• Develop and govern data products, establishing clear ownership, service level agreements, and comprehensive documentation to ensure data assets are trusted and easy to use by various teams. Your focus will be on building governed, well-documented data models that serve as a foundation for analytics, reporting, and machine learning.
• Build and maintain feature stores and reusable analytical components that enable cross-product insights, such as credit behavior, repayment patterns, and customer segmentation. These components will support multiple teams, including credit risk, product development, and decision-making engines.
• Enhance the analytics engineering infrastructure and tooling, working to improve productivity, automation, and testing capabilities within the credit and data organization. Your efforts will help streamline workflows, reduce errors, and accelerate data delivery.
• Ensure consistency and comparability of data models as the Borrowing division expands into new markets and introduces new products. You will establish standards and best practices to maintain data integrity across diverse use cases and geographies.
• Act as a senior technical advisor for the Borrowing data landscape, collaborating with engineering, product, and credit teams to align data strategies with business goals. Your expertise will guide data ingestion, transformation, and consumption practices.
• Influence data practices across the Borrowing domain by establishing architectural patterns, standards, and best practices. You will mentor other engineers and promote a culture of high-quality, scalable data engineering.
• Work closely with data platform engineers on topics such as ingestion patterns, schema evolution, infrastructure costs, and performance optimization. Your technical leadership will help shape the overall data ecosystem.
• Connect technical data decisions to tangible business outcomes, ensuring that data models and systems support strategic initiatives like risk assessment, affordability analysis, and regulatory compliance.
• Communicate complex technical concepts clearly to both technical and non-technical stakeholders, including leadership, to facilitate informed decision-making and strategic planning.
• Lead by example in setting high standards for data quality, reliability, and security, ensuring compliance with relevant regulations and internal policies.
• Stay informed about industry best practices, emerging technologies, and regulatory developments related to data engineering and credit products. Your curiosity and continuous learning will help Monzo stay at the forefront of data innovation.

Requirements

• Proven experience designing scalable, coherent data architectures that support multiple products or domains within a large organization. Your experience should demonstrate the ability to manage complex data environments effectively.
• Demonstrated ability to build governed, documented, and trusted data assets, emphasizing data quality, lineage, and accessibility rather than just creating isolated data models.
• Deep expertise in analytics engineering systems, including proficiency with dbt at scale, data warehouses such as BigQuery or similar platforms, CI/CD pipelines for data, and testing frameworks. Your technical skills will underpin the reliability and maintainability of data systems.
• Experience designing reusable feature layers that serve diverse consumers, including machine learning pipelines, decision engines, and analytics dashboards. Your work will enable teams to data efficiently across different use cases.
• Ability to collaborate effectively with data platform engineers on ingestion patterns, schema evolution, infrastructure costs, and performance tuning. Strong communication and teamwork skills are essential.
• Capacity to connect technical data decisions to business outcomes, understanding how data models impact risk management, product development, and customer experience.
• Leadership qualities to influence and mentor other engineers, set architectural standards, and promote best practices within the team. Your influence will help elevate the overall data engineering maturity.
• Excellent communication skills, capable of articulating technical architectures and strategic plans to both technical teams and executive leadership.
• An interest or curiosity in credit products, including understanding of risk, affordability, regulatory considerations, and how data supports these areas.
• A proactive approach to problem-solving, with the ability to prioritize tasks and manage multiple projects simultaneously.

Nice to have

• Experience working with credit products and understanding the associated data complexities, including risk modeling, regulatory compliance, and customer affordability considerations.
• Familiarity with financial services regulations and data privacy standards relevant to credit and lending.
• Knowledge of additional data tools and platforms that complement the core stack, such as Airflow, Spark, or other orchestration and processing frameworks.

Skills & tools

• dbt for analytics engineering and data modeling
• BigQuery or similar cloud data warehouses
• CI/CD pipelines for data deployment and testing
• Data testing frameworks to ensure data quality and reliability
• Data orchestration tools for managing workflows and dependencies

Practical notes

• Visa sponsorship is available for this role, supporting international candidates who meet the requirements.
• Relocation assistance to the UK can be provided to help candidates move closer to the office locations in Cardiff or London.
• Monzo offers a professional development budget of £1,000 per year, enabling employees to pursue training, certifications, or conferences to enhance their skills.
• The company promotes flexible working hours, allowing employees to balance work and personal commitments effectively.
• This is an on-site role based in Cardiff, London, or at Monzo's UK offices, with the expectation of working from the designated office location.
• Monzo values diversity and inclusion, encouraging candidates from all backgrounds to apply and join its innovative team.