Apache Solr Developer Search Engineer

You will be responsible for designing, developing, and maintaining enterprise-grade search solutions using Apache Solr and SolrCloud. Your key tasks will include developing and optimizing search indexes and schema for various use cases such as product search, document search, or order/invoice search. Additionally, you will be required to integrate Solr with backend systems, databases, and APIs, implementing features like full-text search, faceted search, auto-suggestions, ranking, and relevancy tuning. It will also be part of your role to optimize search performance, indexing throughput, and query response time for efficient results. Your expertise in Apache Solr & SolrCloud, along with a strong understanding of Lucene, inverted index, analyzers, tokenizers, and search relevance tuning will be essential for this position. Proficiency in Java or Python for backend integration and development is required, as well as experience with RESTful APIs, data pipelines, and real-time indexing. Familiarity with Zookeeper, Docker, Kubernetes for SolrCloud deployments, and knowledge of JSON, XML, and schema design in Solr will also be necessary. Furthermore, your responsibilities will include ensuring data consistency and high availability using SolrCloud and Zookeeper for cluster coordination & configuration management. You will be expected to monitor the health of the search system and troubleshoot any issues that may arise in production. Collaboration with product teams, data engineers, and DevOps teams will be crucial for ensuring smooth delivery. Staying updated with new features of Apache Lucene/Solr and recommending improvements will also be part of your role. Preferred qualifications for this position include a Bachelors or Masters degree in Computer Science, Engineering, or a related field. Experience with Elasticsearch or other search technologies will be advantageous, as well as working knowledge of CI/CD pipelines and cloud platforms such as Azure. Overall, your role will involve working on search solutions, optimizing performance, ensuring data consistency, and collaborating with cross-functional teams for successful project delivery.,