Data Engineer at Wise

on-site · full-time · Visa sponsorship

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Responsibilities:
- Own and deliver the end-to-end analytics stack for KYC & Onboarding: ingestion, transformation, modelling, dashboards, and alerting.
- Design, build and maintain core datasets (onboarding events, risk scores, alerts, case outcomes) used for detection, monitoring and reporting.
- Define and execute the analytics infrastructure roadmap for Global KYC & Onboarding.
- Implement and evangelise modern tooling and best practices (dbt, Airflow, Snowflake, Python, Looker/Superset) for reliability, testing, versioning and deployment.
- Instrument pipelines with monitoring, error-handling and data-quality checks appropriate for a regulated environment.
- Partner with product, compliance, risk, analytics and ops to translate data into actionable narratives and KPIs (e.g., time-to-onboard, false-positive rate).
- Identify and onboard new data sources, design tagging strategies and support remediation and control workflows.

Requirements:
- Proven experience building analytics pipelines and data platforms in production using dbt, Airflow, Snowflake and Python.
- Strong data modelling skills and experience producing trusted, documented datasets for analytics and BI.
- Experience designing and implementing data-quality, testing and monitoring practices for sensitive/regulatory domains.
- Familiarity with BI tools (Looker, Superset) and delivering dashboards and stakeholder-ready metrics.
- Excellent cross-functional communication to work with compliance, product and operations teams.
- Comfort with SQL and quantitative troubleshooting; experience with risk scoring, fraud or financial crime detection is a strong plus.
- 5+ years in data engineering or related roles, with a track record of shipping reliable analytics that drive business decisions.