Senior Software Engineer, Data Infrastructure Compute

About the Role

Roblox’s data platform processes petabytes of data daily, powering analytics, ML, and product decisions. The Data Platform Compute team owns the compute layer underneath it: the Kubernetes (EKS) clusters where all of Roblox’s Spark workloads run, and the software that lets engineers, analysts, and ML practitioners submit and run that work reliably and cost-effectively.

As a Senior Software Engineer on this team, you will build and operate the systems that sit between our users and the cluster. These include the Spark job submission service, internal Spark libraries, interactive notebook compute, and cluster lifecycle automation.

Responsibilities

• Build and own core compute platform services: Design, build, and operate the software behind Spark job submission, including APIs, scheduling integration, and user-facing libraries.
• Launch interactive Spark at scale: Deliver Spark Connect to support notebook workflows, including provisioning and managing the EKS compute backing them with proper isolation, resource limits, and cost controls.
• Run a safe, automated cluster fleet: Build fleet management automation for EKS (e.g., blue-green rollouts) that validate new AMIs and Kubernetes versions before production deployment with minimal workload disruption.
• Optimize job performance: Develop auto-tuning systems analyzing Spark history and event logs to recommend or apply configuration changes that improve performance and reduce cost.
• Own batch scheduling on Kubernetes: Operate and upgrade YuniKorn-based scheduling, including queue design, quotas, fairness across tenants, and version upgrades.
• Shape future technology: Evaluate emerging technology such as native Spark acceleration (e.g., Apache Comet), running rigorous benchmarks on Roblox workloads.
• Ensure reliability and cost-efficiency: Define SLOs and metrics, build observability, and drive down toil, incidents, and compute spend across a multi-tenant platform.
• Collaborate cross-functionally: Partner with data engineering, ML, analytics, and infrastructure teams to understand requirements and facilitate migrations.

Qualifications

Required

• 5+ years of experience building and operating production-grade distributed systems or infrastructure platforms.
• Hands-on experience running Apache Spark on Kubernetes (EKS, GKE, or self-managed) as a platform, including executor/driver behavior, resource tuning, and troubleshooting.
• Strong experience operating production Kubernetes clusters at scale (upgrades, node lifecycle, autoscaling, operators/controllers).
• Strong proficiency in at least one of: Go, Java, Scala, or Clojure, with clean and well-tested backend code.
• Experience with AWS (EKS, EC2, IAM, S3) or GCP equivalents, and infrastructure-as-code.
• Experience taking systems from design through production operation, including on-call, incident response, and observability.
• Technical leadership skills: ability to influence design decisions across teams, mentor engineers, and drive alignment.
• B.S. in Computer Science or equivalent practical experience.

Preferred / Bonus Points

• Proficiency in Python.
• Experience with batch schedulers on Kubernetes (YuniKorn, Volcano, Kueue).
• Experience with Spark Connect, Livy, Kyuubi, or other interactive gateway layers for Spark.
• Experience with Spark Operator, Karpenter, Helm, Terraform, or Argo.
• Experience building tooling utilizing Spark event logs/metrics for tuning, cost attribution, or anomaly detection.
• Experience maintaining internal Spark builds or driving Spark version upgrades.
• Familiarity with native execution engines (Comet, Gluten, Velox) or JVM performance tuning.
• Experience migrating workloads from YARN/Hadoop to Kubernetes.
• Contributions to open-source projects in the data or Kubernetes ecosystems.
• Experience operating at consumer-internet scale (100M+ users).