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Senior AWS Engineer/Platform Engineer |

Confidential
Full Timesenior
Navi Mumbai, Maharashtra, INPosted April 20, 2026

Job Description

"Looking for an enthusiastic and talented Elastic Search Engineer with 3-5 years of hands-on experience with Elasticsearch and is eager to work in a fast-paced environment, contributing to the management, optimization, and scaling of our Elasticsearch infrastructure.

Key Responsibilities

  • Elasticsearch Setup & Management:

Install, configure, and manage Elasticsearch clusters (version 8.x), ensuring high availability and performance.

  • Data Ingestion & Indexing:

Assist in the configuration and optimization of data ingest pipelines, index mappings, and document indexing from across various multiple data sources.

  • Query Optimization:

Design and implement efficient queries, aggregations, and filters to ensure optimal search performance.

  • Kibana Dashboards:

Work with Kibana to design and manage dashboards, visualizations, and reporting for various use cases.

  • Data Management:

Monitor and analyze data from various sources being ingested into Elasticsearch clusters, troubleshoot issues, and ensure cluster health.

  • Collaboration:

Collaborate with development teams to ensure proper integration of Elasticsearch with applications.

  • Cluster Monitoring & Performance Tuning:

Monitor Elasticsearch cluster health, optimize queries, and provide insights to improve performance.

  • Documentation:

Maintain clear and concise documentation for Elasticsearch setup, configurations, and processes.

  • Version Upgrade:

Assist in upgrading and maintaining Elasticsearch clusters and tools to the latest 8.x versions.

  • Troubleshooting:

Identify and resolve performance issues, data inconsistencies, and errors in the Elasticsearch environment.

Required Skills

  • Experience:

3-5 years of hands-on experience with Elasticsearch, specifically with version 8.x.

  • Elasticsearch Basics:

Good understanding of Elasticsearch core concepts including nodes, clusters, indices, and shards.

  • Data Modeling:

Familiarity with defining index mappings, custom analyzers, and understanding.

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