L3 Support Engineer – Elasticsearch DB Expert

We are looking for an L3 Support Engineer with deep expertise in Elasticsearch and the ELK stack to provide operational support and drive the stability, performance, and scalability of large-scale cluster deployments. The ideal candidate will play a vital role in diagnosing complex system issues, optimizing performance, and ensuring the reliability of Elasticsearch clusters in production environments.

Key Roles and Responsibilities:

• Provide advanced (L3) technical support for Elasticsearch clusters and associated components (Kibana, Logstash, Beats, metricbeats, etc.).
• Monitor, troubleshoot, and resolve critical production issues related to cluster performance, indexing latency, node failures, and data ingestion bottlenecks.
• Design and maintain ingestion pipelines using Logstash, Beats, or custom shippers to ensure real-time data processing and reliability.
• Optimize Elasticsearch performance by tuning shards, mappings, queries, analyzers, and index templates.
• Manage and implement Index Lifecycle Management (ILM), data retention policies, and archival strategies to maintain cluster health and storage efficiency.
• Perform root cause analysis and work with cross-functional teams to resolve systemic issues.
• Maintain operational documentation and provide knowledge transfer to internal teams.
• Participate in on-call /onsite support and contribute to issue resolution efforts.
• Adhere to high-quality work standards
• Responsible for maintaining Confidentiality, Integrity and Availability of Vehere’s information assets including business critical information.

Skills and Experience:

• Bachelor’s or Master’s degree in Computer Science, Information Technology, or a related field, or equivalent industry experience.
• 5–10+ years of hands-on experience managing Elasticsearch clusters in production (version 7.x/8.x preferred).
• Expert understanding of Elasticsearch internals, including Lucene, inverted indexes, query planning, and data structures.
• Strong command over query DSL, aggregations, filters, and performance tuning techniques.
• Experience designing scalable, resilient architecture for ELK/OpenSearch deployments across multi-node clusters.
• Proficiency in Logstash pipelines, custom grok patterns, and Beats agent configurations.
• Familiarity with Kibana or equivalent visualization tools for dashboarding and troubleshooting.
• In-depth knowledge of JVM tuning, garbage collection (GC) strategies, and heap memory optimization.
• Strong scripting skills in Python, Shell, or Bash for automation, monitoring, and custom ingestion workflows.
• Exposure to DevOps practices, CI/CD pipelines, containerization (Docker), and orchestration tools (Kubernetes) or similar large scale data sets is a plus.