Staff Engineer - Data Platform - Yuno

Europe · Remote · Full Time · Staff-Level Individual Contributor · +8 Years of Experience

Who We Are

At Yuno , we are building the payment infrastructure that allows all companies to participate in the global market. Founded by seasoned experts from the payments and tech industries — including the team behind Rappi, one of Latin America's most ambitious tech companies — our technology provides access to leading payment capabilities, enabling companies to engage customers confidently and maintain global operations through seamless integrations.

We empower high-performing teams at brands like InDrive, McDonald's, Rappi, and Viva Aerobus to connect to 300+ payment methods worldwide via a single API. By leveraging advanced AI and the latest technologies, we orchestrate smart routing and fraud prevention across 80+ countries.

About The Role

We are orchestrating a high-performing data team that works with pace and enthusiasm!

Yuno moves money across borders for companies that can't afford for payments to fail. Our data platform is what makes that visible — to our product teams, our clients, and ourselves.

If you are a Staff Engineer with passion and drive who enjoys solving complex data problems and driving engineering standards and initiatives end-to-end, then we are looking for you.

You will play a pivotal role within the Data team that powers Yuno and its payment platform, while helping co-design and implement an architecture that enables the entire organization to operate on reliable, fast, and trustworthy data.

Your Contribution Will Be

The stack is modern: StarRocks as our primary analytical layer, Flink for processing, DBT for transformation, Airflow for orchestration and various tooling for surfacing insights.

The hard work of making it super reliable is still in front of us — and that's exactly why this role exists.

Technical Leadership

• Define architecture within the data platform, structure and deliver projects and initiatives end-to-end.
• Act as a technical reference point for the Data team, setting quality standards, testing, observability, data modeling, and documentation.
• Lead the design and implementation of scalable, low-latency data pipelines that process high-volume payment transactions in real time.
• Champion an AI-first engineering culture, establishing standards for AI-assisted development, automated data quality testing, and LLM-powered data workflows.

Hands-On Engineering

• Design and build data pipelines for large volumes of payment data that are performant, reliable, and correct — not just fast.
• Design scalable data models that support business-critical use cases: fraud detection, revenue analytics, payment success rate optimization, regulatory reporting.
• Own platform reliability — SLAs, data quality,