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Okta's Data Platform team is seeking an experienced Staff Software Reliability Engineer to design, build, and optimize high-volume, low-latency distributed data systems. You will own foundational infrastructure powering streaming analytics, interactive reporting, and ML platforms that serve the entire organization.
In this role, you'll work across engineering teams to architect and deploy systems handling petabyte-scale data processing. Key responsibilities include designing scalable platform components, conducting design and code reviews, mentoring engineers, debugging production issues, and participating in on-call rotations. You'll have significant influence on the technical direction and implementation of data infrastructure that directly impacts Okta's ability to leverage data and machine learning for security.
The tech stack includes Kinesis, Flink, Elasticsearch, Snowflake, Kafka, Spark, and Kubernetes on AWS. You'll be expected to develop and tune highly scalable distributed systems, understand multithreading and memory management deeply, and bring expertise in data quality, observability, and incident management.
Required: 5+ years industry experience, 2+ years with object-oriented languages (preferably Java), hands-on experience with cloud-based distributed computing (messaging systems, data processing frameworks, storage/compute platforms, orchestrators), and proven track record developing scalable distributed systems.
Nice-to-have: background in security/identity infrastructure, mission-critical high-volume services on major cloud providers, petabyte-scale data integration, Kafka/Hadoop at scale, or Kubernetes on AWS.
