Role & 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.

Preferred candidate profile

- 3 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
- Solid 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.

📌 Search Engineer (Secunderabad)
🏢 TechBlocks
📍 Secunderabad