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Wise

Data Engineer

Posted Yesterday
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Hybrid
London, Greater London, England
Mid level
Hybrid
London, Greater London, England
Mid level
Own and build data infrastructure and analytics pipelines for KYC & onboarding. Develop core datasets, implement modern tooling (dbt, Airflow, Snowflake, Python), ensure data quality, monitoring, and deployment best practices, and partner with cross-functional teams to deliver actionable insights for fraud and compliance decisions.
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Company Description

Wise is a global technology company, building the best way to move and manage the world’s money.
Min fees. Max ease. Full speed.

Whether people and businesses are sending money to another country, spending abroad, or making and receiving international payments, Wise is on a mission to make their lives easier and save them money.

As part of our team, you will be helping us create an entirely new network for the world's money.
For everyone, everywhere.

More about our mission and what we offer.

Job Description

As a Data Engineer in our KYC & Onboarding area, you will own and build the data infrastructure, analytics pipelines and modelling frameworks that detect, prevent and monitor financial crime through customer onboarding. You'll partner closely with product, compliance, analytics, and operations teams to drive data-led insights and proactive controls that enable safe growth.

Key Responsibilities

  • Lead data engineering pipeline related to the onboarding / KYC / FinCrime domain; establish best practices around data modelling, testing, monitoring, and deployment.

  • Define and own the analytics infrastructure roadmap for the Global KYC & Onboarding squad, from data source ingestion through to analytics delivery and dashboard creation.

  • Build and maintain core datasets focused on KYC onboarding events, customer risk scores, alert triggers, and case outcomes.

  • Evangelise and lead adoption of modern tooling (e.g., dbt, Airflow, Snowflake, Python, Looker/Superset) to improve reliability, speed, and trust in analytics.

  • Drive implementation of best practices in data-pipeline instrumentation, monitoring, error-handling, and data-quality in a high-stakes regulatory environment.

  • Together with the Analytics and Product team, translate complex data into clear, actionable narratives for key stakeholders – enabling informed decision-making around customer acceptance or decline, risk tiering, and remediation prioritization.

  • Partner with cross-functional teams (compliance, risk, product, operations) to identify new data sources, define tagging strategies, design KPIs (e.g., average time to onboard, false-positive rate), and deliver measurable business impact.

Additional Information

What you get back:

  • 🚀 RSU's in a growing company

  • 💪 An annual self-development budget

  • ❤️ Statutory maternity leave, with a perk of 18 fully paid weeks of parental leave for birth or adoption

  • ❤️ Paternity leave for 18 weeks at full pay

  • 🌿 3 fully paid ‘me days’ per year to help you manage life

  • 🌍 Relocation and visa expenses covered

  • 🏝️ A paid 6-week sabbatical leave after four years

Interested? Find out more:

  • 👀 How we work – a practical guide

  • 📈 Our Engineering career map

  • ❤️Our values

  • …or check out our Engineering blog.

For everyone, everywhere. We're people building money without borders  — without judgement or prejudice, too. We believe teams are strongest when they are diverse, equitable and inclusive.

We're proud to have a truly international team, and we celebrate our differences.
Inclusive teams help us live our values and make sure every Wiser feels respected, empowered to contribute towards our mission and able to progress in their careers.

If you want to find out more about what it's like to work at Wise visit Wise.Jobs.

Keep up to date with life at Wise by following us on LinkedIn and Instagram.

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