Architect and maintain high-availability Elasticsearch clusters supporting large-scale security event ingestion
Define and enforce Elastic Common Schema (ECS) field mappings across all data sources, ensuring consistent normalization for detection rules and analytics
Design and develop custom data ingestion pipelines using Elasticsearch
Integrate with AWS services including S3, Kinesis Data Streams, Lambda, and CloudWatch for log collection
Manage AWS infrastructure: EC2, S3, IAM, and Secrets Manager
using AWS CloudFormation
Implement data lifecycle management
hot/warm/cold/frozen tier strategies, ILM policies, and snapshot/restore to S3-based data lakes
Partner with Detection Engineering and Threat Intelligence teams to optimize index strategies, queries, and dashboards in Kibana
Establish and maintain cluster security controls: TLS/mTLS, role-based access control (RBAC), audit logging, and encryption at rest
Build resilient, fault-tolerant architectures: cross-cluster replication, shard allocation awareness, and disaster recovery runbooks
Perform activities related to platform health monitoring and upgrade/patching
Troubleshoot and manage production technical issues related to Elasticsearch cloud
Define and enforce SLOs for ingestion latency, query performance, and cluster availability
Mentor junior engineers and establish best practices, runbooks, and architectural standards

Minimum of six years related work experience
Undergraduate degree in a related field or the equivalent combination of training and experience
6+ years of Elasticsearch / Elastic Stack (ELK) experience in a production security or observability environment
Deep understanding of Elastic Common Schema (ECS) and experience mapping diverse log sources (Windows, Linux, network, cloud, EDR) to ECS
Hands-on experience operating Elasticsearch at scale (10TB+/day ingest, 100+ node clusters)
Proficiency with AWS
Kinesis, S3, IAM, CloudTrail, and AWS-native log sources
Experience with data streaming platforms
Apache Kafka, or Confluent Platform
for high-throughput event ingestion
Experience integrating with data lake platforms
AWS S3 / Lake Formation, Data Lake, or Apache Iceberg for long-term retention and threat hunting
Strong understanding of security principles: least privilege, network segmentation, secrets management, audit logging
Experience building resilient systems: replication topologies, capacity planning, chaos engineering mindset, and documented DR procedures
Proficiency with infrastructure-as-code tools (Terraform, Ansible, or CDK)

Lead Engineer, Elasticsearch – SIEM Platform

Key skills