Senior Software Engineer, Data Infrastructure

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. Roblox's data infrastructure processes petabytes of data daily, powering analytics, ML, and product decisions. As a Senior Software Engineer in our Data Infra org, you will design, build, and scale the distributed data infrastructure platforms that power Roblox. You will own and drive the next-generation architecture of our core platforms, which span Kafka, Flink, Spark, Trino, Druid, Airflow and Data Catalog. This role combines high ambiguity and ownership to push the boundaries of what our infrastructure can handle at massive scale, giving you the unique opportunity to steer the evolution of the data landscape. You Will: - Own and Scale Core Platform Components: Take responsibility for the design, architecture, and implementation of 1–2 key data platform frameworks within our stack - Collaborate and Align: Partner with infra, data science, and product engineering teams to ensure your target platform's capabilities are directly guided by platform governance and product requirements. - Optimize Performance at Scale: Dive deep into engine internals, query planning, state management, memory optimization, serialization efficiency to maximize throughput and reliability under heavy load. - Drive Infrastructure Robustness: Lead the design, testing, and operational lifecycle of next-generation infrastructure features running on Kubernetes across cloud environments. - Agentic Interface: Embed AI/ML capabilities within our data platforms, leveraging LLMs for data discovery and generation, building autonomous, self-serve mechanisms for platform interaction layer. You Have: - 5+ years of experience building, designing, testing and maintaining production-grade, large-scale distributed systems. - Data Platform Depth: Deep technical experience building or strong familiarity with at least 1 or 2 foundational technologies within our stack: Kafka, Flink, Spark, Trino, Druid, Airflow, or Data Catalog/Metadata systems. - Strong Engineering Foundations: Robust proficiency in Java, Go, or Scala, with a track record of writing clean, highly performant backend code. - Cloud Fluency: Experience operating and troubleshooting data infrastructure at scale on top of Kubernetes in AWS or GCP. - Technical Leadership: Demonstrated ability to influence technical direction across teams, mentor engineers, and drive alignment on complex cross-cutting initiatives. - B.S. equivalent in CS or sufficient experience. Nice to Have: - Contributions to open-source projects in the data infrastructure ecosystem. - Experience operating infrastructure at consumer-internet scale (100M+ users). For roles that are based at our headquarters in San Mateo, CA: The starting base pay for this position is as shown below. The actual base pay is dependent upon a variety of job-related factors such as professional background, training, work experience, location, business needs and market demand. Therefore, in some circumstances, the actual salary could fall outside of this expected range. This pay range is subject to change and may be modified in the future. All full-time employees are also eligible for equity compensation and for benefits as described on this page. Annual Salary Range $243,290—$295,250 USD Roles that are based in an office are onsite Tuesday, Wednesday, and Thursday, with optional presence on Monday and Friday (unless otherwise noted). Roblox provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws. Roblox also provides reasonable accommodations to candidates with qualifying disabilities or religious beliefs during the recruiting process. For US based roles only, please note the Company may not be able to employ candidates for this role who have United States work authorization related to certain U.S. visa categories, or support future H-1B sponsorship at this time.

5+ years of experience building, designing, testing and maintaining production-grade, large-scale distributed systems. Data Platform Depth: Deep technical experience building or strong familiarity with at least 1 or 2 foundational technologies within our stack: Kafka, Flink, Spark, Trino, Druid, Airflow, or Data Catalog/Metadata systems. Strong Engineering Foundations: Proficiency in Java, Go, or Scala with a track record of writing clean, highly performant backend code. Cloud Fluency: Experience operating and troubleshooting data infrastructure at scale on top of Kubernetes in AWS or GCP. Technical Leadership: Ability to influence technical direction across teams, mentor engineers, and drive alignment on complex cross-cutting initiatives. B.S. equivalent in CS or sufficient experience.

Own and Scale Core Platform Components: design, architecture, and implementation of 1–2 key data platform frameworks within our stack. Collaborate with infra, data science, and product engineering teams to ensure platform capabilities are guided by governance and product requirements. Optimize Performance at Scale: analyze engine internals, query planning, state management, memory optimization, serialization efficiency to maximize throughput under heavy load. Drive Infrastructure Robustness: design, testing, and operational lifecycle of next-generation infrastructure features running on Kubernetes across cloud environments. Agentic Interface: embed AI/ML capabilities within data platforms, leveraging LLMs for data discovery and generation, building autonomous, self-serve mechanisms for platform interaction layer.