ACCLiiVE
Overview
Job Title:
Solr and Elasticsearch Developer
Location:
New York, NY
The company is seeking a skilled and experienced Search Engineer with hands-on expertise in both Apache Solr and Elasticsearch. The ideal candidate will be responsible for designing, developing, and maintaining scalable search solutions that power intelligent search experiences across our platforms. You will work closely with data engineers, backend developers, and product teams to implement advanced search features, optimize indexing pipelines, and ensure high performance and relevance.
Responsibilities
Design and implement scalable search solutions using Solr and Elasticsearch.
Develop and maintain indexing pipelines for structured and unstructured data.
Optimize search relevance using analyzers, tokenizers, stemming, boosting, and custom scoring.
Implement advanced search features such as faceted search, autocomplete, spell correction, and synonyms.
Monitor and tune performance of search clusters, queries, and indexing jobs.
Integrate search services with backend APIs and front-end applications.
Collaborate with cross-functional teams to understand search requirements and deliver solutions.
Ensure high availability, fault tolerance, and security of search infrastructure.
Document architecture, configurations, and best practices.
Required Skills & Qualifications
Bachelor’s or master’s degree in computer science, Engineering, or related field.
7 years of experience in strong hands-on experience with Apache Solr and Elasticsearch (at least 2 3 years with each).
Proficiency in Java, Python, or Scala for backend development and integration.
Experience with search schema design, indexing strategies, and query optimization.
Familiarity with RESTful APIs, JSON, and data modeling.
Experience with log analysis, monitoring tools, and search cluster management.
Knowledge of text analysis, natural language processing (NLP), and information retrieval concepts.
Preferred Qualifications
Experience with search UI frameworks (e.g., React Search UI, Kibana, or custom dashboards).
Familiarity with cloud-based search deployments (AWS OpenSearch, Google Cloud Platform, Azure).
Experience with data ingestion tools like Logstash, Beats, or Apache NiFi.
Exposure to machine learning-based ranking models or semantic search.
Experience with containerization (Docker, Kubernetes) and CI/CD pipelines.
#J-18808-Ljbffr
Solr and Elasticsearch Developer
Location:
New York, NY
The company is seeking a skilled and experienced Search Engineer with hands-on expertise in both Apache Solr and Elasticsearch. The ideal candidate will be responsible for designing, developing, and maintaining scalable search solutions that power intelligent search experiences across our platforms. You will work closely with data engineers, backend developers, and product teams to implement advanced search features, optimize indexing pipelines, and ensure high performance and relevance.
Responsibilities
Design and implement scalable search solutions using Solr and Elasticsearch.
Develop and maintain indexing pipelines for structured and unstructured data.
Optimize search relevance using analyzers, tokenizers, stemming, boosting, and custom scoring.
Implement advanced search features such as faceted search, autocomplete, spell correction, and synonyms.
Monitor and tune performance of search clusters, queries, and indexing jobs.
Integrate search services with backend APIs and front-end applications.
Collaborate with cross-functional teams to understand search requirements and deliver solutions.
Ensure high availability, fault tolerance, and security of search infrastructure.
Document architecture, configurations, and best practices.
Required Skills & Qualifications
Bachelor’s or master’s degree in computer science, Engineering, or related field.
7 years of experience in strong hands-on experience with Apache Solr and Elasticsearch (at least 2 3 years with each).
Proficiency in Java, Python, or Scala for backend development and integration.
Experience with search schema design, indexing strategies, and query optimization.
Familiarity with RESTful APIs, JSON, and data modeling.
Experience with log analysis, monitoring tools, and search cluster management.
Knowledge of text analysis, natural language processing (NLP), and information retrieval concepts.
Preferred Qualifications
Experience with search UI frameworks (e.g., React Search UI, Kibana, or custom dashboards).
Familiarity with cloud-based search deployments (AWS OpenSearch, Google Cloud Platform, Azure).
Experience with data ingestion tools like Logstash, Beats, or Apache NiFi.
Exposure to machine learning-based ranking models or semantic search.
Experience with containerization (Docker, Kubernetes) and CI/CD pipelines.
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