Roman Kagan

• Designed and implemented efficient search and query indexes in OpenSearch for high-performance search capabilities.
• Optimized existing indexes to meet new performance and demand metrics, resulting in a 30% reduction in query response times.
• Led the development of several critical backend components for enterprise applications using Java and SpringBoot, ensuring robust and scalable solutions.
• Developed and deployed serverless applications using AWS Lambda, integrating with ElasticSearch for real-time data processing and DynamoDB for scalable database management.Implemented custom boosting algorithm in Elasticsearch to enhance search relevance and performance for power users, resulting in improved user satisfaction and engagement
• Optimized and reconfigured search architecture by transitioning Solr from Cloudera-managed to standalone mode, enhancing performance and reducing complexity
• Migrated search engine infrastructure from Apache Solr to Elasticsearch, including data transfer and schema conversion, enhancing search performance and scalability
• Leveraged Solr, Grafana, and Prometheus, with integration of solr-exporter, to gather the data to analyze and visualize search metrics for relevance tuning
• Implemented Kibana monitoring and alerting system for quick disaster response across multiple data centers.
• Established a continuous integration and continuous delivery (CI/CD) pipeline using OpenShift, GitLab
• Utilized OpenSource Connection's Quepid, Chorus, and Splainer to debug queries and adjust boosting strategies

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