Our client is a technology-driven organisation building data-intensive platforms where search performance, relevance, and scalability are critical. They are looking to hire an Elasticsearch Developer with strong backend engineering experience to help design, build, and optimise high-performance search and analytics solutions.
This role is suited to developers from C#, Java, or similar server-side backgrounds who enjoy working with large data sets, distributed systems, and search-driven applications.
Key Responsibilities
* Design, implement, and optimise Elasticsearch indices, mappings, and queries.
* Build and maintain scalable search and analytics solutions using Elasticsearch.
* Integrate Elasticsearch with backend services written in C#, Java, or similar languages.
* Tune search relevance, performance, and scalability for high-volume systems.
* Work with structured and unstructured data to support advanced search use cases.
* Collaborate with product, data, and engineering teams to define search requirements.
* Monitor, troubleshoot, and resolve performance and reliability issues in Elasticsearch clusters.
* Contribute to architectural decisions around data pipelines, indexing strategies, and query design.
* Stay up to date with Elasticsearch features, best practices, and ecosystem tools.
Required Skills & Experience
* Strong experience working with Elasticsearch in a production environment.
* Solid backend development experience in C#, Java, or a similar language.
* Good understanding of distributed systems and search architecture.
* Experience designing and optimising queries, aggregations, and relevance scoring.
* Familiarity with index lifecycle management, sharding, and replication strategies.
* Experience working with REST APIs and integrating search into backend services.
* Understanding of performance tuning and troubleshooting in search-heavy applications.
Desirable / Nice to Have
* Experience with Logstash, Beats, or Elasticsearch ingest pipelines.
* Exposure to Kibana for monitoring, dashboards, or analytics.
* Cloud experience (AWS, Azure, or GCP), including managed Elasticsearch services.
* Knowledge of containers, Docker, and CI/CD pipelines.
* Experience handling large-scale data ingestion and real-time search.
* Familiarity with SQL and/or NoSQL data stores alongside Elasticsearch.