The posting, in Roblox's own words
archived Oct 21, 2026Every 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.
Your Role:
Roblox's data infrastructure processes petabytes of data daily, powering analytics, ML, and product decisions for a platform serving 200M+ daily active users. As a Senior Software Engineer on our Real-time Analytics Platform team , you will design, build, and scale the core OLAP infrastructure powering sub-second analytical queries across Roblox. Our team directly owns and operates StarRocks and Apache Druid , driving high-throughput streaming ingestion and low-latency MPP query processing. You will lead the next-generation architecture of our real-time analytics platform, combining high ownership and deep technical complexity to push the boundaries of MPP engine performance, streaming ingestion pipelines, and cluster scalability.
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You Will:
Own and Scale Core OLAP Platforms : Take end-to-end ownership of the architecture, operational health, and scalability of our high-throughput OLAP engines, specifically StarRocks and Apache Druid . Optimize Query Engine Performance : Dive deep into engine internals, cost-based optimization (CBO), query planning, vectorized execution, memory optimization, and serialization efficiency to maximize throughput and maintain sub-second latency under heavy concurrent load. Architect Streaming Ingestion Pipelines : Design, build, and optimize real-time data ingestion paths leveraging Apache Kafka , Apache Flink and native engine load mechanisms. Drive OLAP Data Modeling Best Practices : Partner with infra, data science, and product engineering teams to guide data modeling for MPP databases, optimizing partitioning, bucketing, sort keys, and materialized views. Manage Cluster Infrastructure & Capacity : Lead cluster provisioning, lifecycle management, operations, and capacity planning using Kubernetes and across cloud environments. Advance Autonomous Interfaces : Integrate AI/ML and -driven capabilities within our query platforms to enable automated self-serve mechanisms and intelligent data discovery for engineers.