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

1. 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.
2. 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.