Senior Data Engineer, Economy

Every day, tens of millions of people come to Roblox to explore, create, play, learn, and connect with friends in 3D immersive digital experiences– all created by our global community of developers and creators.

At Roblox, we’re building the tools and platform that empower our community to bring any experience that they can imagine to life. Our vision is to reimagine the way people come together, from anywhere in the world, and on any device. We’re on a mission to connect a billion people with optimism and civility, and looking for amazing talent to help us get there.

A career at Roblox means you’ll be working to shape the future of human interaction, solving unique technical challenges at scale, and helping to create safer, more civil shared experiences for everyone.

Who We Are:

Shape the future of Roblox’s virtual economy.

The Economy ML team is building the machine learning backbone that powers Roblox’s Marketplace, Developer Monetization, and Payments ecosystems. From intelligent pricing and personalized storefronts to dynamic layout optimization and avatar understanding, we’re reimagining how the Roblox economy drives user engagement, monetization, and creator success at scale.

As a Senior Software Engineer (Data Systems), you will architect, build and deploy high-scale, reliable real-time and batch data systems for personalization, search and recommendation across various product surfaces in Marketplace, Developer Monetization and Payments. You will be involved in key data projects from architecting event taxonomies and logging interfaces to real-time feature serving across multiple search and recommendation surfaces.

What You’ll Do

• Act as data engineer for Economy ML, setting standards for batch vs streaming feature pipelines, table design, observability, and documentation used across the Economy group.

• Work as a hands-on contributor on our data systems to power content recommendation, search and personalization across Economy product surfaces.

• Partner with Product, Data Science and ML engineering counterparts to prioritize data initiatives that unlock top-line business goals and reduce tech debt in existing datasets and pipelines.