Elasticsearch Admin

Role & responsibilities

Job Title: Elasticsearch Admin
Position: Lead Analyst
Experience: 8 - 10 Years
Category: Software Development/ Engineering
Shift: General
Main location: Hyderabad
Employment Type: Full Time
Education Qualification: Bachelor's degree in Computer Science or related field or higher with minimum 7 years of relevant experience.

Position Description: Works independently under limited supervision and applies knowledge of subject matter in Applications Development. Possess sufficient knowledge and skills to effectively deal with issues, challenges within field of specialization to develop simple applications solutions. Second level professional with direct impact on results and outcome.

Your future duties and responsibilities

• Design, implement, and manage highly available, scalable, and secure self-hosted Elasticsearch clusters in production environments.
• Architect and optimize enterprise search platforms using Elasticsearch, Kibana, and Logstash (ELK Stack).
• Develop and enhance semantic search capabilities using Elasticsearch Learned Sparse Encoder (ELSER), vector search, and hybrid search techniques.
• Design and implement search relevance tuning strategies, including custom analyzers, synonyms, ranking algorithms, boosting, and query optimization.
• Build REST APIs and search services using Python and Java for indexing, querying, and search automation.
• Lead Elasticsearch cluster administration activities, including performance tuning, capacity planning, monitoring, upgrades, and security hardening.

Required qualifications to be successful in this role
Must-Have Skills:

• 810 years of experience in Elasticsearch administration and search platform architecture.
• Strong expertise in Elasticsearch, Kibana, Logstash, and the Elastic Stack (ELK).
• Experience designing, deploying, and managing self-hosted Elasticsearch clusters.
• Hands-on experience with Elasticsearch cluster administration, performance tuning, and capacity planning.
• Strong knowledge of search relevancy tuning, ranking algorithms, analyzers, tokenizers, synonyms, and query optimization.
• Experience with semantic search, hybrid search, vector search, and Elasticsearch Learned Sparse Encoder (ELSER).
• Proficiency in Python and/or Java for developing search services and automation.
• Experience implementing disaster recovery (DR), backup/restore, snapshots, and cross-cluster replication (CCR).
• Strong understanding of index design, mappings, shard allocation, Index Lifecycle Management (ILM), and ingestion pipelines.
• Experience with REST APIs and Elasticsearch Query DSL.
• Knowledge of Linux system administration and shell scripting.
• Experience with monitoring and troubleshooting using Kibana, Prometheus, Grafana, or Elastic monitoring.
• Strong understanding of Elasticsearch security, RBAC, TLS, authentication, and authorization.
• Experience with Docker, Kubernetes, and CI/CD pipelines.
• Strong problem-solving, performance optimization, and production support skills.

Good-to-Have Skills:

• Experience with Knowledge Graphs and metadata management.
• Familiarity with AI-powered search, Retrieval-Augmented Generation (RAG), and Large Language Model (LLM) integrations.
• Experience with vector databases and embedding models.
• Knowledge of Apache Kafka, Apache Spark, or other streaming technologies.
• Experience with cloud platforms such as AWS, Azure, or Google Cloud Platform (GCP).
• Infrastructure as Code (IaC) experience using Terraform or Ansible.

Preferred candidate profile