Staff Software Engineer – Extreme Platform ONE (10548) at Extreme Networks in San Jose, CA

Job description

Over 50,000 customers globally trust our end-to-end, cloud-driven networking solutions. They rely on our top-rated services and support to accelerate their digital transformation efforts and deliver unprecedented progress. Become part of something big with Extreme! As a global networking leader, learn why there is no better time to join the Extreme team. Position details Title of position: Staff Software Engineer Position type: Full time - Onsite Location: San Jose, CA Position reports to: Sr Manager of Software Systems Engineering Application deadline: Applications are being accepted on a rolling basis and this posting will remain open until filled. Work authorization: We are unable to sponsor or take over sponsorship of an employment visa, including H-1B visas, at this time Job Description: Extreme Networks is seeking a highly skilled Staff Software Engineer to lead Performance Monitoring efforts for our Enterprise Platform ONE (EP1). This role is critical for building and scaling the data pipeline that ingests, enriches, and persistently stores platform telemetry at high volume, while maintaining strong security engineering practices and a performant, reliable infrastructure. The successful candidate will own the data ingestion and storage architecture, drive performance and scalability improvements, and keep the platform's code and dependencies secure. Scope: Design, build, and scale a high-throughput data platform supporting enterprise-grade performance monitoring and analytics. Develop and optimize data streaming, processing, and storage solutions using technologies such as Kafka, Numaflow, ClickHouse, TimescaleDB, and Elasticsearch. Collaborate closely with platform, data, and engineering teams to deliver scalable, reliable, and high-performance solutions. Drive continuous improvement in platform performance, scalability, reliability, and operational efficiency. Stay current with emerging technologies and best practices , with opportunities for professional development through certifications and technical training. Key Responsibilities Data Platform Engineering Design and build real-time data ingestion pipelines using Kafka and Numaflow to process high-volume platform telemetry and monitoring events. Architect enrichment pipelines that transform raw event data into contextualized, actionable performance signals. Own the persistent storage strategy across ClickHouse, TimescaleDB, and Elasticsearch, matching each data store to the right access pattern, and optimize queries, indexing, and partitioning to meet latency and throughput targets at scale. Design data retention, rollup, and partitioning strategies that balance query performance with storage cost. Tune the EP1 performance monitoring platform to handle growing data volume and query concurrency. Identify and resolve bottlenecks across the full pipeline, from Kafka consumer lag to storage-layer query plans. Design for horizontal scalability, including partitioning, sharding, and load distribution across data stores. Establish capacity planning and load-testing practices for the platform's data infrastructure. Build, Deployment & Collaboration Support pre-deployment verification, including performance regression testing and security checks. Collaborate with QA to validate data pipeline correctness and system resilience under load. Apply secure coding practices and participate in code reviews with a security lens. Maintain documentation of system architecture, data flows, and operational runbooks. Partner with engineering, data, and platform teams on design reviews and technical decisions. Basic Qualifications: 8+ years of software engineering experience, including significant experience building and scaling data pipelines and/or observability platforms. Strong hands-on experience with Kafka (or similar streaming platforms) for high-throughput data ingestion. Experience with Numaflow or similar stream-processing/dataflow frameworks. Deep expertise in ClickHouse, Timesc