Data analyst - AML

About the team:

At SumUp, keeping our platform safe and compliant is critical to the trust of the millions of small businesses we serve around the world.

You’ll join our Global AML team at an exciting point in its growth.

We’re expanding into new markets, evolving our AML capabilities, introducing AI-enabled controls, and navigating increasingly complex regulatory expectations.

As an AML Data Analyst, you’ll play a key role in turning AML data into actionable insights.

Working closely with our global AML Operations and AML Governance teams, as well as colleagues across Engineering and Data, you’ll help us understand how our controls are performing, identify risks and gaps early, and make better decisions as our business scales.

This is a role where your analysis will go beyond reporting.

The insights you generate will directly support how we monitor, improve, and strengthen our global AML framework.

What you’ll do:

• Build and maintain AML dashboards, operational reports, and data packs used by AML Operations, AML Governance, and senior leadership
• Design measurement frameworks that track AML operational KPIs, including case volumes, productivity, SLA adherence, and screening hit rates
• Support AML teams by providing data extracts, analysis, trend identification, and root-cause analysis on AML control outputs and data quality issues
• Run data validation and quality checks to keep AML data accurate and consistent across systems and regions
• Support Transaction Monitoring and Sanctions/PEP screening through data analysis, requirements definition, and testing
• Partner with Engineering and AML Operations to define data requirements and support automation projects
• Build self-service analytics resources so AML Operations teams can explore data and find insights independently

You’ll be great for this role if you have:

• Experience in data analytics, business intelligence, or a similar role within financial services, fintech, compliance, AML, or another regulated environment.
• Strong SQL skills, including writing complex queries and building reliable datasets for reporting and analysis.
• Practical experience with Python for data analysis and automation.
• Experience working with a cloud data warehouse such as Snowflake.