ELK Engineer

ELK Engineer - L2

Experience: 3-6 Years

Role Level: L2 / Mid-Level Engineer

Domain: ELK / SIEM / Log Management / Platform Engineering

Role Summary

We are looking for a hands-on ELK Engineer - L2 to manage, troubleshoot, optimize, and support Elasticsearch-based SIEM/log-management environments. The engineer will independently handle complex ELK issues, platform performance, log ingestion, cluster management, and production stability.

Key Responsibilities

• Install, configure, administer, upgrade, and troubleshoot Elasticsearch, Logstash and ProAct environments.
• Manage Elasticsearch clusters, nodes, indices, shards, replicas, mappings, templates and ILM policies.
• Monitor and optimize JVM/heap, CPU, memory, disk utilization, indexing and search performance.
• Troubleshoot cluster health, unassigned shards, disk watermark, indexing failures, mapping conflicts and performance degradation.
• Develop, enhance and troubleshoot Logstash pipelines, Grok/Dissect patterns and ECS mappings.
• Diagnose log loss, ingestion delays, parsing failures, pipeline-routing and data-quality issues.
• Support ingestion through Elastic Agent/Filebeat, Syslog, APIs, Kafka and Redis.
• Perform capacity planning and optimize storage, retention, shards, indices and pipeline throughput.
• Manage backup, snapshot, restore and DR/recovery readiness.
• Configure and troubleshoot Kibana dashboards, visualizations, data views and access-related issues.
• Perform RCA for P1/P2 and recurring platform issues and drive permanent corrective actions.
• Build scripts/automation for health checks, monitoring, deployment and repetitive operational activities.
• Maintain SOPs, KEDB, troubleshooting guides and technical documentation.
• Provide technical guidance and KT to L1 engineers and independently coordinate complex issues with Product/Engineering teams.

Required Technical Skills

Must Have: Elasticsearch, Logstash, Kibana, Linux, Grok/Regex, ECS, cluster management, shards/indices, ILM, JVM/heap, performance tuning and troubleshooting.

Good to Have: Elastic Agent/Filebeat, Kafka, Redis, Python/Shell scripting, REST APIs, Git, SQL, AWS/Azure/GCP, SIEM and cybersecurity fundamentals.

Expected L2 Competency

The candidate should independently manage and troubleshoot an end-to-end ELK environment, from log ingestion and parsing through Elasticsearch indexing, storage and visualization.

The engineer should be capable of handling production incidents, RCA, cluster optimization, capacity/performance issues and complex ingestion problems with minimal dependency on senior engineers.

Key Success Measures

• ELK platform availability and stability
• Reduced P1/P2 incidents and faster MTTR
• Cluster and storage optimization
• Minimal log loss and ingestion delay
• Improved indexing and search performance
• Reduction in recurring issues through RCA and automation
• Quality of SOP/KEDB and knowledge transfer