{"id":2038209,"url":"https://alion.io/job/sisa-elk-engineer","title":"ELK Engineer","company":{"id":2144267,"name":"SISA","domain":"sisa.ai","url":"https://alion.io/company/sisa-ai","size_band":"51-200","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Keka","truth_index":{"grade":"B","score":75,"open_postings":9,"ghost_share":0,"stale_share":1,"repost_share":0,"time_to_fill_p50_days":null,"computed_at":"2026-10-12T06:55:09Z"}},"role":"Industrial Engineering","role_family":"Industrial Engineering","seniority":"middle","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":[],"countries":[],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":null,"experience_years_min":3,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Amazon ECS","optional":false},{"name":"Apache Kafka","optional":false},{"name":"ElasticSearch","optional":false},{"name":"Filebeat","optional":false},{"name":"Kibana","optional":false},{"name":"Linux","optional":false},{"name":"Logstash","optional":false},{"name":"Platform Engineering","optional":false},{"name":"Redis","optional":false},{"name":"SIEM","optional":false},{"name":"AWS","optional":true},{"name":"Azure","optional":true},{"name":"GCP","optional":true},{"name":"Git","optional":true},{"name":"Python","optional":true},{"name":"Rest API","optional":true},{"name":"SQL","optional":true}],"status":"live","first_seen_at":"2026-10-07T15:49:46Z","employer_posted_date":"2026-10-07","last_verified_at":"2026-10-12T23:53:27Z","board_verified":true,"closed_at":null,"days_open":5,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":5},"description":"ELK Engineer - L2\nExperience: 3-6 Years\nRole Level: L2 / Mid-Level Engineer\nDomain: ELK / SIEM / Log Management / Platform Engineering\nRole Summary\nWe 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.\nKey Responsibilities\nInstall, configure, administer, upgrade, and troubleshoot Elasticsearch, Logstash and ProAct environments.\nManage Elasticsearch clusters, nodes, indices, shards, replicas, mappings, templates and ILM policies.\nMonitor and optimize JVM/heap, CPU, memory, disk utilization, indexing and search performance.\nTroubleshoot cluster health, unassigned shards, disk watermark, indexing failures, mapping conflicts and performance degradation.\nDevelop, enhance and troubleshoot Logstash pipelines, Grok/Dissect patterns and ECS mappings.\nDiagnose log loss, ingestion delays, parsing failures, pipeline-routing and data-quality issues.\nSupport ingestion through Elastic Agent/Filebeat, Syslog, APIs, Kafka and Redis.\nPerform capacity planning and optimize storage, retention, shards, indices and pipeline throughput.\nManage backup, snapshot, restore and DR/recovery readiness.\nConfigure and troubleshoot Kibana dashboards, visualizations, data views and access-related issues.\nPerform RCA for P1/P2 and recurring platform issues and drive permanent corrective actions.\nBuild scripts/automation for health checks, monitoring, deployment and repetitive operational activities.\nMaintain SOPs, KEDB, troubleshooting guides and technical documentation.\nProvide technical guidance and KT to L1 engineers and independently coordinate complex issues with Product/Engineering teams.\nRequired Technical Skills\nMust Have: Elasticsearch, Logstash, Kibana, Linux, Grok/Regex, ECS, cluster management, shards/indices, ILM, JVM/heap, performance tuning and troubleshooting.\nGood to Have: Elastic Agent/Filebeat, Kafka, Redis, Python/Shell scripting, REST APIs, Git, SQL, AWS/Azure/GCP, SIEM and cybersecurity fundamentals.\nExpected L2 Competency\nThe candidate should independently manage and troubleshoot an end-to-end ELK environment, from log ingestion and parsing through Elasticsearch indexing, storage and visualization.\nThe engineer should be capable of handling production incidents, RCA, cluster optimization, capacity/performance issues and complex ingestion problems with minimal dependency on senior engineers.\nKey Success Measures\nELK platform availability and stability\nReduced P1/P2 incidents and faster MTTR\nCluster and storage optimization\nMinimal log loss and ingestion delay\nImproved indexing and search performance\nReduction in recurring issues through RCA and automation\nQuality of SOP/KEDB and knowledge transfer","description_format":"text","description_chars":2868,"description_truncated":false,"requirements":{"experience_years_min":3,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":null,"security_clearance":false,"languages":[]},"benefits":[],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":["Artificial 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