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Data Engineer

This position is no longer available

It may have been filled or removed by Wise

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Requirements

  • Lead data engineering pipeline related to the onboarding / KYC / FinCrime domain
  • Define and own the analytics infrastructure roadmap for the Global KYC & Onboarding squad
  • 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)
  • Drive implementation of best practices in data-pipeline instrumentation, monitoring, error-handling, and data-quality in a high-stakes regulatory environment
  • Translate complex data into clear, actionable narratives for key stakeholders
  • Partner with cross-functional teams to identify new data sources, define tagging strategies, design KPIs, and deliver measurable business impact

What You'll Be Doing

  • 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

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AI Summary ✨
Wise logo

Wise

Greater London, UK

Experience: Senior
Posted: May 19, 2026
Last seen: 3 days ago
Python
dataengineering

Why we track Wise

Wise (formerly TransferWise) is a London-based fintech that built international money transfers from scratch. They have major engineering hubs in Tallinn, London, and Budapest. The engineering challenges around real-time payments, compliance, and multi-currency infrastructure are technically deep.

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