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Senior Analytics Engineer - Risk Analytics

SumUp
Berlin, GermanyPosted 30 April 2026

Job Description

About the Risk Analytics Team: SumUp is looking for a Senior Analytics Engineer to join the Risk Analytics Team within the Risk Compliance Tribe. This is a high-impact, technically demanding role where you will help ensure SumUp meets its regulatory obligations across European entities while building the data foundations that power fraud, chargeback, and compliance analytics. The Risk Analytics Team sits at the intersection of data, regulation, and business integrity. The team is responsible for regulatory reporting across multiple European regulatory entities, as well as for data products supporting fraud and chargeback analysis and broader Risk Compliance initiatives. The team works in close collaboration with Data Scientists, Data Engineers, and backend engineers to deliver reliable, accurate, and scalable data solutions. As a Senior Analytics Engineer, you will be the cornerstone of the team's technical capability. Your work will directly influence the team's ability to scale its regulatory reporting, automate critical pipelines, and deliver trusted data products that support decision-making across the Risk Compliance Tribe. This is a unique opportunity to work at the intersection of data modeling, compliance, and business impact in a fast-growing global fintech. What you'll do : Build and maintain complex data models that track merchant activity, delivering trusted data marts suitable for accurate and timely regulatory reporting. Develop, improve, and maintain the pipelines used to submit regulatory reports across European entities, ensuring compliance with varying reporting frequencies and GRC requirements, maintaining the focus on reducing manual effort and increasing reliability. Develop and own data validation strategies required by regulators, ensuring every report meets the expected quality standards. Ensure all data products follow dbt best practices and maintain the dbt project by applying coding guidelines and style validations. Collaborate with Data Engineers, Data Scientists, Software Engineers, and backend engineers to correctly and reliably integrate their outputs into data pipelines. Monitor and control the computing expenses of the domain, proactively identifying opportunities to improve cost-efficiency. Extract pipeline metrics and present them through clear, accessible dashboards to support team-wide monitoring. Contribute to a robust data infrastructure (Git, Argo Workflows, dbt, Snowflake) that empowers Data Analysts and stakeholders with self-service analytics. You’ll be great for this role if you have: 5+ years of professional experience in tech, startups, data warehousing, or analytics. Strong, hands-on knowledge of dbt — including project ownership, coding guidelines, best practices, and the automated enforcement of those guidelines. Solid SQL skills with experience designing, building, and managing complex data models in a cloud data warehouse (ideally Snowflake), with a focus on performance and maintainability. Development experience in Python for pipeline development and automation. Experience with Git and CI/CD workflows. Strong ability to analyze complex data issues and provide robust, scalable data products. Strong problem-solving and analytical skills, with the ability to communicate clearly with both technical and non-technical stakeholders. Ability to manage multiple priorities and stakeholders effectively across teams and tribes. Nice to have: Experience with data mesh architecture Experience in fintech and transactional data models. Experience with pipelines orchestration and scheduling. Experience with AWS. Why you should join SumUp: 🌍 Opportunity to work with SumUppers globally on large-scale fintech products used by millions of businesses worldwide, from our Berlin office. This involves an office-first setup 🌈 Commitment to Diversity and Inclusion: Be part of a workplace that values and promotes diversity, fostering an inclusive environment where everyone ... (truncated, view full listing at source)
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