Key Responsibilities:
- Design, deploy, and maintain Elastic Stack environments, including Elasticsearch, Kibana, Logstash, Beats, and Fleet.
- Build and optimize ingestion pipelines, index strategies, search queries, dashboards, and automation workflows.
- Write scripts, automation, and integrations (Python, PowerShell, Bash, etc.) to streamline operations, data processing, and monitoring.
- Deploy Elastic across platforms, including on-premises, public cloud (AWS, Azure, GCP), GovCloud, and containerized environments (Kubernetes, Docker, OpenShift).
- Leverage automation and orchestration tools such as Terraform, Ansible, CI/CD pipelines, and Docker to manage deployments and operational tasks.
- Integrate Elastic with enterprise tools such as SIEMs, Splunk, CrowdStrike, and other telemetry sources.
- Monitor system health, troubleshoot performance issues, and optimize for reliability and scalability.
- Lead design reviews, provide guidance on Elastic best practices, and support knowledge sharing across teams.
- Maintain documentation for architectures, deployment patterns, runbooks, and operational best practices.
- Stay current with Elastic features, certifications, and emerging platform capabilities.
- Must have a Secret Clearance
- Elastic Certification is a big plus
- Must have tech stack: Elastic / ECK / Kubernetes - Would consider solid Elastic and Kubernetes exp that doesn't have ECK
- Deep, hands-on expertise with Elastic Stack (Elasticsearch, Kibana, Logstash, Beats, Fleet).
- Strong scripting and automation skills (Python, PowerShell, Bash, etc.).
- Solid understanding of observability, logging, metrics, and distributed systems.
- Experience designing, deploying, and optimizing production-scale Elastic environments.
- Strong Linux/Unix, networking, and cloud platform knowledge (AWS, Azure, GCP).
- Ability to mentor, guide, and influence engineering teams on Elastic best practices.
- Prior experience in DevOps, Site Reliability Engineering, or cloud platform roles is a plus.
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