Job
Description
We are looking for a highly skilled Elasticsearch Database Architect & Designer with 8-10 years of relevant experience in designing, implementing, and optimizing Elasticsearch clusters. The ideal candidate will have a deep understanding of Elasticsearch architecture, query optimization, data indexing, and high-availability design. You will play a crucial role in ensuring scalability, performance, and security of Elasticsearch deployments while integrating them into enterprise applications and cloud environments. Key Responsibilities Architect, design, and implement scalable, resilient, and high-performance Elasticsearch clusters. Define indexing strategies, mapping configurations, and shard allocation to optimize search performance. Ensure high availability, disaster recovery, and failover strategies for mission-critical applications. Develop multi-cluster and cross-cluster search solutions for large-scale distributed environments. Indexing, Querying & Performance Optimization Optimize Elasticsearch queries, aggregations, and filters to improve search efficiency. Implement index lifecycle management (ILM) for data retention and archiving strategies. Fine-tune Elasticsearch sharding, caching, and thread pool settings to maximize throughput. Implement RBAC (Role-Based Access Control), authentication, and encryption using X-Pack Security. Ensure compliance with data security standards like GDPR, HIPAA, etc. Design and develop data ingestion pipelines using Logstash, Beats, and custom connectors. Integrate Elasticsearch with various data sources (SQL/NoSQL databases, message queues, APIs). Monitoring & Maintenance Set up monitoring and alerting using Kibana, Prometheus, and Elastic Stack monitoring. Perform proactive cluster health checks, backup/restore, and index management. Deploy and manage Elasticsearch in AWS, Azure, or GCP using Terraform, Kubernetes, or Helm. Automate cluster provisioning and scaling using CI/CD pipelines and Infrastructure as Code (IaC). Write automation scripts using Python, Bash, or Golang for cluster maintenance. Integrate Elasticsearch with backend services using Java, Python, or Node.js.
