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You'll improve search latency and relevancy using large scale data systems and machine learning. You have experience with large scale data processing technologies (e.g. Spark, Flink, Kafka, Airflow, YARN/Hadoop.
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Deep familiarity with one or more of the following areas at scale: Lucene-based search systems (ElasticSearch or Solr), search ranking and retrieval, data science, or information taxonomy.
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This is a full-time position reporting to the Sr. Engineering Manager of our Search and Recommendation team. Excellent in analysis, modeling and problem-solving, and can see the essence of problems from complex data.
$127,000 - $165,000 a yearExpandApply NowActive JobUpdated Yesterday - UpvoteDownvoteShare Job
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Must have technologies: Java, Mongo DB, Elastic Search, Solr, Content/Document Management. 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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Experience with data access optimization for Cassandra, PostgreSQL and Solr/Elastic search and Lucene. We're seeking engineers with fresh ideas spanning information retrieval, distributed computing, large-scale system design, networking and data storage, artificial intelligence, and natural language processing.
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Deep familiarity with one or more of the following areas at scale: Lucene-based search systems (ElasticSearch or Solr), search ranking and retrieval, data science, or information taxonomy Bachelor or advanced degree in computer science or a related field or equivalent experience.
$127,000 - $165,000 a yearFull-timeExpandUpdated 3 days ago - UpvoteDownvoteShare Job
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Experience with Big Data technologies such as AWS, Hadoop, Spark, Pig, Hive, Lucene/SOLR or Storm/Samza. Experience in building large-scale machine-learning infrastructure for online recommendation, ads ranking, personalization, or search, etc.
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Experience with data intensive analytical solutions leverages relational (Redshift, Oracle), non-relational (Postgres, Aurora, Graph databases) and search-based data platforms (SOLR, Open Search.
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Experience with large scale enterprise applications using big data open-source solutions such as Spark, Kafka, Elastic Search / Solr and Hadoop, HBase. - 4+ years of experience in architecture for commercial scale data pipelines.
ExpandApply NowActive JobUpdated 5 days ago - UpvoteDownvoteShare Job
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5+ years of experience in SRE/DevOpsStrong Knowledge of Search Systems i.e. SolrExtensive experience in managing the applications on AWSExperience with Kubernetes, Spark, Hadoop, Cassandra, Redis, AWS S3, and Elasticsearch/Solr/Lucene.
ExpandApply NowActive JobUpdated 2 days ago - UpvoteDownvoteShare Job
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The application is a large-scale structured data search and discovery tool running in an AWS environment with broad mission adoption. Experience using relational databases such as PostgreSQL or MySQL; document databases such as Elasticsearch or Solr; or big data technologies such as Hadoop, Hive, or Spark.
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Managing distributed teams is a plusProven track record of building products/features using Natural Language Processing, Query Understanding and Semantic Search techniquesExperience with Big Data and search technologies Spark/Hadoop/Kafka and SOLR.
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Experience querying against different search technologies such as SOLR or Elasticsearch. Team members work in a multitasking, quick-paced, dynamic, process-improvement environment that requires experience with large-scale (Terabytes) database and application development, large-scale file manipulation, data modeling, data mapping, data testing, and data quality.
Full-timeExpandApply NowActive JobUpdated 7 days ago - UpvoteDownvoteShare Job
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GENERAL DUTIES:You will help manage large-scale data storage environments, maintain the existing network systems, provide new architectures and scalable solutions to solve complex enterprise search problems.
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Create efficient data messaging and access solutions for Kafka, Cassandra, and PostgreSQL databases. Key QualificationsProficiency in software programming with Java, Python, and Spark for data analysis and feature extraction.
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