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Production support role of Hadoop ecosystem including Sqoop, Spark, Hive, HDFS, Impala, Kafka. Production support role of Hadoop ecosystem including Sqoop, Spark, Hive, HDFS, Impala, Kafka.
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Experience with Big Data technologies and developing in Hadoop ecosystem, i.e. Hadoop, Hbase, Hive, Scala, SPARK, Sqoop, Flume, Kafka, Python. Familiarity with Azure DevOps (ADO), Jenkins, Artifactory, and similar systems along with experience in Unix/Linux shell scripting.
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Knowledge in open-source technologies and the Hadoop ecosystem - EMR, Spark, Python, Hive, HDFS, Kafka, etc. Knowledge in open-source technologies and the Hadoop ecosystem - EMR, Spark, Python, Hive, HDFS, Kafka, etc.
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Enhance the Hadoop and Spark ecosystem to provide data users a reliable and scalable infrastructure. Enhance the Hadoop and Spark ecosystem to provide data users a reliable and scalable infrastructure.
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Experience with Hadoop ecosystem components - HDFS, YARN, MapReduce & cluster management tools like Ambari or Cloudera Manager and related technologies. We are hiring a Senior Hadoop Admin / Platform Engineer to join our Digital Engineering team.
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3+ years of experience with distributed data/computing tools (MapReduce, Hadoop, Hive, EMR, Kafka, Spark, Gurobi, or MySQL) The Machine Learning Experience (MLX) team supports an internally hosted Model Training ecosystem running critical infrastructure for machine learning and data analysis across Capital One. You will get an opportunity to collaborate on the 1000's of models being trained on the platform by 4000+ users and dive deep into the unique engineering challenges we have around compute, data access, security and scale.
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Utilize programming languages like Java, Python, SQL, Node, Go, and Scala, Open Source RDBMS and NoSQL databases, Container Orchestration services including Docker and Kubernetes, and a variety of AWS tools and services.
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Hands-on experience on Apache Hadoop ecosystem components like MapReduce, Sqoop, Pig, Hive, HBase, Spark, Kafka, Oozie, Flume, Zookeeper. Job Description : 8+ years of extensive IT experience with multinational clients working in diverse fields of software development lifecycle with experience in Big Data/Hadoop Ecosystem.
ExpandApply NowActive JobUpdated 8 days ago - UpvoteDownvoteShare Job
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Design and implement distributed data processing pipelines using Spark, Hive, Python, Airflow, and other tools and languages prevalent in the Hadoop ecosystem. Design, Develop, Modernize/Migrate pipelines to DatabricksDevelop applications on Cloud preferably AWSExplore and build proof of concepts using open source NOSQL technologies such as HBase, DynamoDB, Cassandra and Distributed Stream Processing frameworks like Apache Spark, Kafka stream.
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Minimum 6 years of experience with a technology such as Apache Hive or Apache Pig and distributed processing platforms such as Apache Spark or MapReduce and experience working in the Hadoop ecosystem and experience working with a nosql database such as MongoDB or Accumulo.
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Extensive technical skills covering:Microsoft technologies; JAVA and J2EE; Service-Oriented Architecture (SOA) and Web Services (SOAP/REST/Microservices); Hadoop ecosystem; Linux environment; Relational (RDBMS) and Non-relational (NoSQL) databases; E-commerce and Mobile platforms; AWS cloud services; Containerization with Docker (Swarm, Kubernetes); Elasticsearch, MongoDB, Redis (master/slave/sentinel); CI/CD pipelines using Jenkins, Ansible, Rundeck, and JFrog Artifactory.
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Requirements: Requires a Bachelor’s degree (or foreign equivalent) in Computer Engineering, Computer Science, or related field and 5 years of progressively responsible, post-baccalaureate experience as a Data Analytics Manager, Data Engineering Manager, Software Developer, or related position involving Big Data analysis in Retail and Commercial Banking domain in Hadoop ecosystem.
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Data Integration, Data Security on Hadoop ecosystem. Experience with Big Data Analytics & Business Intelligence andIndustry standard tools integrated with Hadoop ecosystem.
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This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Center 2 (19050), United States of America, McLean, VirginiaSenior Software Engineer, Back End (Python, Kubernetes, AWS)Do you love building and pioneering in the technology space.
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Experience with Hadoop ecosystem (HDFS, Hive, Yarn, File formats like Avro/Parquet), Kafka, Spark Streaming, PySpark, Airflow. Experience with Hadoop ecosystem (HDFS, Hive, Yarn, File formats like Avro/Parquet), Kafka, Spark Streaming, PySpark, Airflow.
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