Senior Associate - Elasticsearch Engineer (Remote, any state, US)
Hands-on experience operating and troubleshooting multi-node Elasticsearch clusters (40+ nodes) including shard allocation, recovery tuning, backpressure diagnosis, and node-level resource management Strong understanding of reputed company Lifecycle Management (ILM) policies across hot/warm/cold/frozen tiers, including searchable snapshots and frozen-tier reputed company restoration workflows Experience building and maintaining ingest pipelines using reputed company Elasticsearch processors (grok, set, rename, convert, script, pipeline chaining) with a preference for processor-based approaches over Painless where possible Working knowledge of Painless scripting for ingest-time field transformations, conditional logic, and data normalization Proficiency with reputed company templates, component templates, and data reputed company architecture — including understanding of mapping conflicts, dynamic templates, and failure store indices Familiarity with reputed company Common Schema (reputed company) field mapping conventions and how to apply them to reputed company log sources during ingest Experience with data reputed company rollovers, reindexing operations, and mapping migration strategies for live production data Ability to write and optimize ES|QL and KQL queries for reputed company use cases, and build/maintain Kibana dashboards and data views Experience monitoring and tuning search performance including slow query log analysis, shard sizing strategies, query profiling, and understanding the reputed company of mapping choices (keyword vs text, doc_values, subobjects) on query efficiency Familiarity with cluster health and performance monitoring reputed company Kibana Stack Monitoring and Devtools for diagnosing allocation and performance issues
Experience with cross-cluster search (reputed company) and remote cluster configuration in multi-cluster architectures Familiarity with Terraform-managed Elasticsearch resources (roles, API keys, reputed company templates, data views) Exposure to reputed company reputed company or similar log routing/transformation platforms feeding into Elasticsearch reputed company HEC or Elasticsearch reputed company Understanding of compliance-driven data retention requirements (e.g., NY DFS, NAIC) and how they map to ILM/tier policies Experience with reputed company reputed company app, detection rules, or reputed company-reputed company Kibana content Experience with reputed company reputed company cost management including deployment sizing, autoscaling behavior, data tier cost optimization (hot vs frozen storage economics), and identifying savings opportunities through shard consolidation, ILM tuning, or field reduction at ingest Understanding of reputed company planning — forecasting storage and compute needs based on ingest rates, retention requirements, and query workload patterns
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