Search Engineer

Key Responsibilities: Design and implement robust, scalable search architectures using Solr and Elasticsearch. Write, optimize, and maintain complex search queries (including full-text, faceted, fuzzy, geospatial, and nested queries) using Solr Query Parser and Elasticsearch DSL. Work with business stakeholders to understand search requirements and translate them into performant and accurate queries. Build and manage custom analyzers, tokenizers, filters, and index mappings/schemas tailored to domain-specific search needs. Develop and optimize indexing pipelines using Apache Spark for processing large-scale structured and unstructured datasets. Perform query tuning and search relevance optimization based on precision, recall, and user engagement metrics. Create and maintain query templates and search APIs for integration with enterprise applications. Monitor, troubleshoot, and improve search performance and infrastructure reliability. Conduct evaluations and benchmarking of search quality, query latency, and index refresh times. Required Skills and Qualifications: 4 to 5 years of hands-on experience with Apache Solr and/or Elasticsearch in production environments. Proven ability to write and optimize complex Solr queries (standard, dismax, edismax parsers) and Elasticsearch Query DSL, including: Full-text search with analyzers Faceted and filtered search Boolean and range queries Aggregations and suggesters Nested and parent/ child queries Strong understanding of indexing principles, Lucene internals, and relevance scoring mechanisms (BM25, TF-IDF). Proficiency with Apache Spark for custom indexing workflows and large-scale data processing. Experience with document parsing and extraction (JSON, XML, PDFs, etc.) for search indexing. Experience integrating search into web applications or enterprise software platforms.