Lead Analytics Engineer

• Lead and mentor Analysts within one of Wise's squads, establishing best practices around infrastructure, monitoring, testing, and data modelling. • Define and drive the data infrastructure roadmap for your assigned tribe, ensuring strategic alignment and efficient execution. • Build and maintain core datasets, ensuring data quality and accessibility across the organisation. • Become the go-to expert for tooling such as dbt and AI applications, leading adoption and rollout across the organisation. • Strategically assess and implement data modelling best practices within your squad to elevate Wise's data capabilities. • Support over 130 Analysts and 2,500+ weekly active BI tool users by making it easy to find the right data quickly.

• Have advanced proficiency in SQL and Python. • Have proven experience building robust analytics pipelines and designing effective data models. • Have hands-on experience with an orchestration tool such as Airflow. • Have strong project management and communication skills with a track record of driving initiatives. • Have excellent data storytelling ability, translating complex insights into clear, actionable narratives. • Be able to build strong empathy for stakeholders and internal customers, proactively identifying and solving their problems. • Have experience driving best practices around Business Intelligence tools such as Looker or Superset.

• Have experience with dbt for data transformation and modelling. • Have experience leading or mentoring other analysts or analytics engineers. • Have familiarity with AI applications in a data or analytics engineering context. • Have experience working in a high-growth fintech or globally distributed data team.

• Mentor Analysts directly on infrastructure, monitoring, testing, and data modelling best practices. • Own and drive the data infrastructure roadmap for your assigned tribe. • Build and maintain core datasets with a focus on quality and accessibility. • Lead adoption of new tooling including dbt and AI-powered analytics applications. • Implement and champion data modelling best practices across squads. • Collaborate closely with stakeholders to proactively identify and solve data problems.

We have been Wise customers for years and have always had a great experience. We love their transparent approach in everything they do, from showing the correct exchange rates to disclosing all their fees, and even being honest about how they work. Founded in 2010 in London, Wise is now a publicly traded company operating in over 160 countries, generating 1.2+ billion pounds in revenue (2025) and is highly profitable. What we especially love at Wise is their work from anywhere policy after 6 months: Basically you can remotely work from (almost) anywhere in the world for up to 90 days a year. As they are solving a massive problem and are strongly mission-driven, we are sure that any individual passionate about working on complex, impactful problems in sending money globally efficiently, while continuing to work on the much-loved Wise solutions, will love working there.

• Earn £85,000–£125,000 gross per year based on experience and interview outcomes. • Receive Restricted Stock Units (RSUs). • Access flexible working — whether that's working from home, school plays, or life admin. • Receive paid annual holiday, sick days, parental leave, and other leave opportunities. • Take 6 weeks of paid sabbatical after 4 years at Wise, on top of annual leave. • Join a truly international team that celebrates diversity and inclusion.

Wise is a global technology company building the best way to move and manage the world's money — with min fees, max ease, and full speed. With over 130 Analysts and more than 2,500 weekly active users of its Business Intelligence tools, Wise's Analytics Engineering team is central to helping the company build better products, faster by making data insights easy to access for everyone across the organisation.