Why this role stands out
This hybrid Elasticsearch Engineer role offers a fantastic opportunity to leverage your extensive Elastic Stack administration and security operations expertise to solve complex cybersecurity challenges within a reputable organization. You'll thrive here if you're a mid-senior level professional with a passion for innovation and a drive to build cutting-edge security analytics solutions, and we encourage you to apply!
Quick overview
Job description
Top Skills' Details
- 5+ years of experience administering Elastic Stack, including Elasticsearch, Kibana, Logstash, Beats, or Fleet
- Experience managing Elasticsearch index lifecycle policies, index templates, and data streams at scale, and building Kibana dashboards, visualizations, and lens-based analytics for security operations Job Description
- 5+ years of experience administering Elastic Stack, including Elasticsearch, Kibana, Logstash, Beats, or Fleet
- Experience managing Elasticsearch index lifecycle policies, index templates, and data streams at scale, and building Kibana dashboards, visualizations, and lens-based analytics for security operations
- Experience with Elastic Security detection rules, alerts, and case management workflows
- Experience with log ingestion pipeline design, including parsing, enrichment, and normalization across heterogeneous log sources such as network, endpoint, identity, and cloud
- Experience with Elastic Common Schema (ECS) and mapping non-standard log sources into ECS-compliant fields
- Experience working in government cybersecurity environments such as SOC, SIEM operations, or defensive cyber
- Experience optimizing log collections from AWS platform, endpoints, and network devices
- Knowledge of AI/ML concepts as applied to security analytics such as anomaly detection, behavioral baselining, or threat scoring
- Abily to obtain a Secret clearance
- Bachelor’s degree Nice to Have Skills
- Experience working in an agile working environment
- Experience working with DoD clients
- Experience with Elastic's ML jobs, including for User and Entity Behavior Analytics (UEBA), rare process detection, or anomalous login patterns
- Experience with Elastic AI Assistant or integration of LLMs into Elastic Security workflows such as natural language querying and alert triage assistance
- Experience building or fine-tuning ML models outside Elastic, including Python, scikit-learn, and PyTorch, for security use cases such as threat detection or lateral movement scoring
- Experience with Elastic Agent fleet management at scale, including custom integrations and policy management
- Experience with cross-domain data flows and working in multi-classification environments such as IL4, IL5, or IL6
- Experience with ES|QL or EQL for advanced threat hunting and detection-as-code workflows
- Kubernetes Certification such as Kubernetes and Cloud Native Certification or Kubernetes Application Developer Certification
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