Wise is a global technology company focused on moving and managing the world’s money. As a Data Engineer in the KYC & Onboarding area, you will own and build the data infrastructure, analytics pipelines, and modeling frameworks that detect, prevent, and monitor financial crime throughout customer onboarding. You will partner with product, compliance, analytics, and operations to drive data-led insights and proactive controls that enable safe growth.
Wise is a global technology company focused on moving and managing the world’s money. As a Data Engineer in the KYC & Onboarding area, you will own and build the data infrastructure, analytics pipelines, and modeling frameworks that detect, prevent, and monitor financial crime throughout customer onboarding. You will partner with product, compliance, analytics, and operations to drive data-led insights and proactive controls that enable safe growth.
Key responsibilities: - Lead data engineering pipelines related to onboarding, KYC, and FinCrime; establish best practices around data modeling, testing, monitoring, and deployment. - Define and own the analytics infrastructure roadmap for the Global KYC & Onboarding squad, from data source ingestion through analytics delivery and dashboards. - Build and maintain core datasets focused on KYC onboarding events, customer risk scores, alert triggers, and case outcomes. - Evangelize and lead adoption of modern tooling (dbt, Airflow, Snowflake, Python, Looker/Superset) to improve reliability, speed, and trust in analytics. - Drive implementation of data-pipeline instrumentation, monitoring, error-handling, and data quality in a high-stakes regulatory environment. - Collaborate with Analytics and Product to translate complex data into clear, actionable narratives for stakeholders to support decisions on 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., av
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Key responsibilities: - Lead data engineering pipelines related to onboarding, KYC, and FinCrime; establish best practices around data modeling, testing, monitoring, and deployment. - Define and own the analytics infrastructure roadmap for the Global KYC & Onboarding squad, from data source ingestion through analytics delivery and dashboards. - Build and maintain core datasets focused on KYC onboarding events, customer risk scores, alert triggers, and case outcomes. - Evangelize and lead adoption of modern tooling (dbt, Airflow, Snowflake, Python, Looker/Superset) to improve reliability, speed, and trust in analytics. - Drive implementation of data-pipeline instrumentation, monitoring, error-handling, and data quality in a high-stakes regulatory environment. - Collaborate with Analytics and Product to translate complex data into clear, actionable narratives for stakeholders to support decisions on 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., av
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