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Experience managing NoSQL databases/search engines such as Elasticsearch, Redis, DynamoDB, MongoDB, etc. Mastery of native JavaScript, with experience using Node.js and any front end frameworks such as Angular, Vue.js, React, etc.
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Proficiency in Elasticsearch query DSL and search query optimization. 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.
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Experience using Elasticsearch/Kibana or data visualization software (Tableau, ArcGIS, Analyst Notebook). As the team's User Support Specialist, you will provide DTP software familiarization and discovery tradecraft to enable Intelligence Community (IC) users to search for and retrieve relevant data to support intelligence analysis and operations.
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Full text indexing and searching technologies such as Lucene and ElasticSearch, tuning indexing and searching for search relevancy and accuracy; using data mining and machine learning tools and algorithms.
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May recommend data analytics strategies including enterprise data warehousing, master data management, data quality, data governance, Big Data, business intelligence, visualization. May provide guidance for enterprise initiatives for data governance, metadata, data stewardship, data quality, master data management.
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Marathon TS User Support Specialist (Intelligence Data Discovery and Tradecraft) - TS/SCI Defense Intelligence Agency (DIA) Bethesda, MD (Hybrid) Marathon TS is seeking a User Support Specialist, who will be designing, developing, deploying, and operating a DoD-wide Tasking, Collection, Processing, Exploitation, and Dissemination (TCPED) workflow management platform for Open-Source Intelligence (OSINT.
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Two (2) years of experience must include: Java; J2EE; JMS; SOA; OOAD; OOP; Eclipse IDE, IntelliJ; Server-side application frameworks, including JSP, Servlet, Struts and Spring, Springboot; ORMs, including Hibernate; Restful and SOAP-based web services, including JSON and XML; SolR search, ElasticSearch; Apache Kafka; Unit testing frameworks, including Junit and Jest; Logging utility - Log4J; Jenkins; and SQL Data Store – Oracle.
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Demonstrated experience with backend database and search systems such as Elasticsearch, JanusGraph, DataStax Graph, PostgreSQL, Mysql/MariaDB, SQLite. Demonstrated experience as a full stack developer, including frontend and backend development with technology stacks such as SpringBoot, Django, Flask, Angular, jQuery, or React.
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Preferred Skills: 2+ years of experience with enterprise search technologies like IBM Watson, OpenSearch, ElasticSearch, Solr. Proficiency in working with cloud databases in complex environments requiring high performance and scalability.
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Leverage Elasticsearch, Java, Angular, TypeScript, Node.js, python and other technologies in the support of various facets of the Lab’s enterprise search application including crawling, indexing, query tuning, report building, and updating the search APIs and User Interfaces.
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Experience with Big data technologies to include Data Ingest (JSON, Kafka, Microservices, Elastic Search), Analytics (HIVE, SPARK, R, PIG, OOZIE workflows), Elasticsearch, Hadoop (HIVE data, OOZIE, Spark, PIG, IMPALA, HUE), COTS Integration (Knowi, MongoDB, Oracle, MySQL RDS, Elastic, Logstash, Kibana, Zookeeper, Consul, HADOOP/HDFS), Docker and Chef.
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Key Skills: Node / Node JS; Go; Git (GitHub, GitLab, BitBucket, SVN); GCP; Docker; AWS; API; Dynatrace; ELK Stack (Elastic Search, Logstash, Kibana); FaaS; Google Kubernetes Engine (GKE); Hashicorp Vault; Java; JavaScript.
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As an expert member of the security product team, your responsibilities will include shaping the product strategy and roadmap for the Elastic Security solution, specifically focusing on cost-effective long-term storage, search, and analysis of security events and information using stateless Elasticsearch and other Elastic technologies.
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DSL-based Search : multiple large-scale Elasticsearch Clusters searched using our Disco Query Language (DQL), Vector Search. Persistence: Elasticsearch, Cassandra, SQL data stores, others.
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Demonstrated expertise in search indexing, retrieval and ranking systems like Elasticsearch/OpenSearch, personalization, and/or natural language processing. We are looking for a highly-skilled and experienced machine learning engineer to join the Search team to lead our search quality efforts through their early ML phase (and beyond.
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