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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. Development skills around Hadoop, Spark, PySpark, Hive.
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Service Management~ Administer, configure, and maintain Hadoop ecosystem services within both Cloudera Data Platform (CDP) and Cloudera Distributed Hadoop (CDH), including HDFS, YARN, Hive, Spark, Ranger, Sentry, Kerberos security, KMS, KTS, Zookeeper, and more.
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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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Hands on experience working on Hadoop ecosystem (Hadoop , Hive , HBase , PIg) GCP Java 1.6+, Spring Boot, Spring MVC, Hadoop , Hive, HDFS, Map Reduce, Spark Batch & Spark Streaming, Scala, Kafka.
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Knowledge of Hadoop ecosystem and strong hands-on experience on SQL,Hadoop, Hive and Spark. We are Hiring for Big Data Engineer at Nucleusteq. Good experience in developing big data applications on cloud environment like GCP, AWS, Azure.
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Deep understanding of modern data processing technology stacks: Spark, HBase and other Hadoop ecosystem technologies. Deep understanding of modern data processing technology stacks: Spark, HBase and other Hadoop ecosystem technologies.
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3 8 years of hands on experience working with ETL Hadoop Knowledge of various components of Hadoop ecosystem and experience in applying them to practical problems Hive Impala Spark Strong knowledge of working with relational databases like Teradata DB2 Oracle Sql server.
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Expert knowledge and experience in Databricks, Lake House, Structured Streaming, Kafka, Delta Lake, Delta Live table, Delta shareetc. Explore 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.
RemoteExpandApply NowActive JobUpdated 9 days ago - UpvoteDownvoteShare Job
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Design, develop, and maintain high volume Java and Scala based data processing jobs using industry standard tools and frameworks in the Hadoop ecosystem, such as Spark, Kafka, Hive, Impala, Avro, Flume, Oozie, and Sqoop.
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Experience with Hadoop ecosystem components - HDFS, YARN, MapReduce & cluster management tools like Ambari or Cloudera Manager, and related technologies. Hands on and strong understanding of Hadoop architecture.
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Possess deep technical skills to turn big data in Teradata and Hadoop into actionable insights and ability to think about the big picture and connect the dots to evaluate how the insights impact eBay’s ecosystem.
$149,200 - $234,850Full-timeExpandApply NowActive JobUpdated 6 days ago - UpvoteDownvoteShare Job
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Experience in distributed data (structured, semi-structured, unstructured, streaming) processing techniques using Apache Spark, Hadoop, Hive, Kafka, and big data ecosystem technologies preferred.
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Familiarity with the Hadoop ecosystem and related tooling (Spark, HDFS, Databricks). Experience with online game service APIs, particularly Xbox Live, Sony NP, Steam, and Epic Games. Familiarity with the Hadoop ecosystem and related tooling (Spark, HDFS, Databricks.
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Proven experience with MPP databases like Teradata and reasonable experience with Hadoop ecosystem products like Hive, HDFS, HBASE etc. Proven expertise and experience in creating a microservice using Flask or FastAPI or R equivalent for a machine learning model.
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Preferred Qualifications:Sound Knowledge of Software engineering design patterns and practicesStrong understanding of Functional programming and RESTful APIsExperience in Big data ecosystem using Hadoop, Spark, Scala, Python packages and libraries for large scale data is preferred.
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