Staff Software Engineer – Extreme Platform ONE (10548)
Extreme Networks· enterprise· Networking· Oct 1, 2026 · 27d ago
San Jose, California, United States
In office
Full-time
Staff
$170K–$190K
8+ years exp
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, TimescaleDB, or other time-series/columnar databases, including schema design and query optimization.
Experience with Elasticsearch for search and analytics at scale.
Strong query optimization skills across SQL, time-series, and search-oriented data stores.
Proficiency in multiple programming languages (Go, Java, Python, or similar).
Solid understanding of container security, Kubernetes, and cloud infrastructure.
Experience with CI/CD pipelines and build systems.
Working knowledge of security scanning tools and common vulnerability types (OWASP Top 10, CWE).
Bachelor's degree in Computer Science or related field, or equivalent professional experience.
Preferred Qualifications:
Experience designing multi-tenant, high-cardinality time-series data platforms.
Background in observability or monitoring platforms (metrics, logs, traces).
Experience with stream-processing and data enrichment pipelines at scale.
Knowledge of capacity planning, load testing, and performance benchmarking.
Familiarity with container security scanning and secure coding practices.
Experience with API security testing and web application security.
Security certifications (CEH, Security+, or similar) a plus, not required.
Data Platform & Storage:
Streaming/Ingestion: Kafka, Numaflow
Storage: ClickHouse, TimescaleDB, Elasticsearch
Query optimization, indexing, and partitioning strategies
Engineering & Infrastructure:
Languages: Java, Python, Go, C#, JavaScript
Build Systems: Maven, Gradle, npm, pip, cargo
Version Control: Git, GitHub, GitLab
Cloud Platforms: AWS, Azure, GCP
Container Technologies: Docker, Kubernetes, container registries
CI/CD: Jenkins, GitLab CI, GitHub Actions, Azure Pipelines
IaC: Terraform, CloudFormation, Ansible
Soft Skills:
Attention to detail and strong analytical thinking
Excellent written and verbal communication skills
Ability to work independently and manage multiple priorities
Proactive problem-solving and troubleshooting abilities
Passion for building scalable, reliable data systems
Salary based on qualifications, experience and region up to USD 170 k to 190K plus benefits.
Equal Employment Opportunity
Extreme Networks, Inc. is an Equal Opportunity Employer. Qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or status as a protected veteran. We are committed to taking affirmative action to employ and advance in employment qualified protected veterans, including disabled veterans, recently separated veterans, active-duty wartime or campaign badge veterans, and Armed Forces service medal veterans.
Extreme Networks also strives to prevent other, subtler forms of inappropriate behavior (for example, stereotyping) from ever gaining a foothold in our organization. Whether blatant or hidden, barriers to success have no place at Extreme Networks. We encourage people from underrepresented groups to apply.
Fair chance and background checks
Extreme Networks will consider qualified applicants with criminal histories in a manner consistent with the California Fair Chance Act, Los Angeles Fair Chance Initiative for Hiring Ordinance, Los Angeles County Fair Chance Ordinance for Employers, Philadelphia Fair Criminal Record Screening Standards Ordinance, Illinois Human Rights Act, Cook County Human Rights Ordinance, Seattle Fair Chance Employment Ordinance, and the San Francisco Fair Chance Ordinance. An applicant's conviction history will not be considered until after a conditional offer of employment has been made. Following any individualized assessment, applicants will be provided with the opportunity to respond before any adverse action is taken.
Extreme Networks does not seek salary history information from applicants and will not rely on salary history in determining whether to offer employment or in setting compensation.
Application prep
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Keywords to mirror
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Benefits
Benefits detected in the listing.
Professional Development