As an Elastic Stack Engineer, a typical day involves designing, implementing, and supporting enterprise search, log analytics, and observability solutions using Elasticsearch, Kibana, and Logstash. The role focuses on data ingestion, search optimization, dashboard development, monitoring, alerting, and production support within cloud-native environments.

Roles & Responsibilities
Perform independently as a Subject Matter Expert (SME) in Elasticsearch, Kibana, and Logstash.
Design and manage Elasticsearch indices, mappings, shard strategies, and Index Lifecycle Management (ILM) policies.
Build and optimize Elasticsearch Query DSL searches, aggregations, and search performance.
Develop and maintain Logstash pipelines for data ingestion, transformation, enrichment, and routing.
Integrate data sources using Elastic Agent, File beat, Metric beat, Fluent, Syslog, Kafka, and application log streams.
Implement event enrichment using tagging, correlation identifiers, and geolocation data.
Develop Kibana dashboards, visualizations, reports, and alerting solutions for operational and business users.
Configure role-based access control (RBAC), spaces, security policies, and user permissions.
Deploy and manage Elastic Stack components using Docker, Kubernetes, Elastic Cloud on Kubernetes (ECK), and Helm.
Configure platform security, including TLS, authentication, Single Sign-On (SSO), and API keys.
Monitor cluster health, storage utilization, ingestion performance, and search efficiency.
Troubleshoot indexing issues, ingestion failures, dashboard problems, and platform incidents.
Support upgrades, deployment validation, rollback procedures, and release management activities.
Perform root cause analysis and maintain technical documentation.
Participate in production support and on-call activities.
Professional & Technical Skills
Must-Have Skills
Elasticsearch, Kibana, and Logstash (Primary Skills).
Strong experience with Elasticsearch mappings, analyzers,



Query DSL, aggregations, shard sizing, replica management, and ILM.
Hands-on experience developing Logstash pipelines, including Grok, Dissect, filtering, and data transformation.
Experience building Kibana dashboards, visualizations, reports, and alerts.
Experience with File beat, Metric beat, Elastic Agent, Fluent, or Fluent Bit.
Experience deploying and operating Elastic Stack on Docker and Kubernetes platforms.
Strong knowledge of JSON, regular expressions, structured logging, and data ingestion concepts.
Scripting experience using Bash or Python.
Experience with Git, CI/CD pipelines, and configuration management.
Ability to diagnose cluster performance, ingestion bottlenecks, search latency, and node health issues.
Experience supporting production environments and incident resolution.
Valuable-To-Have Skills
Experience in OTT, Streaming, Broadcast, or Digital Media platforms.
Experience with Elastic APM and distributed tracing.
Knowledge of Painless scripting, ingest pipelines, and runtime fields.
Experience with Kafka-based event ingestion.
Experience with Cross-Cluster Search (CCS), Cross-Cluster Replication (CCR), Snapshot and Restore, and disaster recovery strategies.
Experience with Amazon OpenSearch Service.
Knowledge of Elastic Security, SIEM, and threat monitoring solutions.
Experience with Terraform, AWS Cloud Development Kit (AWS CDK), or AWS CloudFormation.
Experience with Grafana, Datadog, Open Telemetry, and observability platforms.
Familiarity with ServiceNow, Jira Service Management, and IT Service Management (ITSM) processes.
Additional Information
Minimum 3 years of relevant experience in Elastic Stack engineering.
Total experience requirement: 5 years (3+2 model).
Elasticsearch, Kibana, and Logstash are mandatory skills.
Experience in observability, monitoring, and log analytics environments is preferred.
Participation in production support and on-call activities may be required."
Comments for Suppliers:
Elastic Stack (ELK)

📌 Elastic Stack Engineer (Hyderabad)
🏢 TRIGENT SOFTWARE PRIVATE
📍 Hyderabad