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Search tools: Solr, Lucene, Elasticsearch. Data science tools/languages: R, R Studio, Python (data preparation and analysis libraries), Databricks, etc. Our data exploitation approach is tightly integrated with Human-Centered Design and DevSecOps.
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Any level of experience with Lead design and development of the Big Data Analytics Platform by gathering requirements from the various stakeholders and converting it to technical design and implementation using various Big Data technologies like Apache Spark, Mapreduce, Mongodb etc and programming languages like Java, Scala, Python and build and maintain search related product using technologies including Lucene and Elasticsearch.
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You've used several data storage technologies like Elasticsearch, Solr, PostgreSQL, MongoDB, or Cassandra and have some idea how they work and why they work that way. This is a senior software engineering role that focuses on enhancing the vector similarity search functionality within Elasticsearch, covering the design and implementation of new vector search features, enhancements to existing vector search functionality, and resolving bugs.
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Elasticsearch and Kibana or similar visualization tools for search and indexing of data. React JS and its associated libraries and tools (e.g., Redux, React Router, Jest, Enzyme.
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As a Senior Elasticsearch Engineer, you will play a pivotal role in designing, implementing, and optimizing our Elasticsearch infrastructure to support our growing data and search needs.
Full-timeExpandUpdated 11 days ago - UpvoteDownvoteShare Job
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Understanding of database design concepts (Pluggable DB's) and data modeling for relational or nonrelational databases such as RDBMS (Oracle/Postgres), No SQL (MongoDB, Cassandra) or NewSql (Cockroach DB) and search DB's like Elasticsearch incorporating multi-master across multi-regions.
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Worked with time series DBs, metric collection frameworks, message bus and other aspects of data streaming and analytics platforms using Apache Kafka, OpenTSDB, ElasticSearch, Splunk or equivalent technologies.
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We're looking for a top-notch search engineering leadership in the area of information retrieval, search indexing, Elasticsearch, Lucene, algorithms, relevance & ranking, data mining, machine learning, data analysis & metrics, query processing, multi-lingual search, and search UX. This is an opportunity to make a huge impact in a fast-paced, startup-like environment in great company.
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Ability to develop search optimization algorithms on large datasets using technologies such like Elasticsearch, ESRI Geoportal etc. This position will be located at the Mississippi State University Science and Technology Center at the Stennis Space Center, MS to provide computer science support in the development of data management capabilities and visualization techniques for the National Oceanographic and Atmospheric Administration (NOAA) and its partners.
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Our backing data sources are a document-based storage solution (currently MongoDB), with Oracle as a relational database component, Elasticsearch as a search indexing technology, and Hadoop for larger data / reporting needs.
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Experience generating performant and accurate real-time search results based on large data sets using ElasticSearch, PostgreSQL, and other database and search engine technologies.
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Familiarity with non-relational data technologies, for example graph databases, key-value databases (Redis, AWS DynamoDB), search/analytics engines (ElasticSearch), vector databases etc.
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REQUIRED KNOWLEDGE/SKILLS: Extensive experience with Angular (or another modern front end framework such as: React or Vue.js) Expert knowledge of Javascript, HTML, and CSS. Experience designing complex search interfaces.
$150,000 - $275,000 a yearFull-timeExpandUpdated 11 days ago - UpvoteDownvoteShare Job
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Nice to haves: integration with Microsoft tools, knowledge of Alfresco Document management, COOP, Large scale database experience include MongoDB, ElasticSearch, Ignite, CockroachDB, percona DB and MySQL.
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Hands on experience with Text Mining and Text Search applications and frameworks like Elasticsearch or Solr or Lucene. 8+ years of experience in algorithms, machine learning, and natural language processing to build complex data driven software applications.
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