Data Engineer

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.

• Lead data engineering pipeline related to the onboarding / KYC / Fin Crime 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.

• RSUs in a growing company
• An annual self‑development budget
• Statutory maternity leave, plus 18 fully paid weeks of parental leave for birth or adoption
• Paternity leave for 18 weeks at full pay
• Three 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