ELK Architect or Senior Elasticsearch Engineer

ELK Observability Lead

Descriptions:
"
•       Lead the design, implementation, and ongoing enhancement of the ELK Stack (Elasticsearch, Logstash, Kibana) to deliver enterprise-wide observability, logging, and monitoring capabilities.

•       Own the observability strategy by collaborating with cross-functional teams to translate business and operational requirements into scalable dashboards, alerts, and reporting solutions for diverse stakeholders.

•       Drive performance optimization and reliability of the ELK platform, including proactive monitoring, troubleshooting, and fine-tuning of Elasticsearch clusters for high-volume data ingestion, storage, and retrieval.

•       Oversee the development and governance of data ingestion pipelines using Logstash and other tools, ensuring robust, scalable, and reliable data flow from multiple heterogeneous sources.

•       Enable advanced observability use cases by delivering meaningful analytics and intuitive data visualizations in Kibana to support IT operations, incident response, and business insights.

•       Establish and enforce best practices for security, data governance, access control, and compliance within the ELK ecosystem.

•       Act as a technical leader and SME for observability, mentoring team members, driving capability building, and providing guidance on ELK best practices and modern observability approaches.

•       Work closely with DevOps, SRE, and application teams to integrate observability into CI/CD pipelines and ensure end-to-end visibility across systems and services."

" Elasticsearch (Expert level)
Distributed Architecture & Cluster Design
Search & Index Optimization (Query DSL, Aggregations)
Performance Tuning & Scaling
ILM, Data Streams, Sharding Strategy
•       Prior experience in AIOps, ITOM, or observability solutions.
•       Familiarity with scripting and automation (e.g., Python, Bash).
•       Knowledge of infrastructure-as-code tools like Terraform or Ansible."