Search Engineer

Job description

• 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.

• 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.