software engineer - Oklahoma City, United States - Spry Info Solutions INC

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    Description


    We are looking for a candidate who will work closely with a global team of other big data engineers and software developers on the Hadoop platform and play a key role in the team.


    Responsibilities:
    Develop the Microservices based RESTful API's using Spring MVC framework by writing controller, service, DAOs classes and business logics using java api and data structures
    Design multiple MapReduce programs for data extraction, transformation and aggregation in XML, JSON, CSV and other compressed file formats.
    Develop the spark code using Scala and Spark-SQL for data cleaning, pre-processing and aggregation. Apply the spark RDD transformations on top of Hive external tables.
    Develop complex hive queries for different file sources and writing Hive UDFs. Conduct performance tuning of hive queries.
    Coordinate the cluster and shedule workflows using Zookeeper and Oozie. Create HBase-Hive integration tables and loading large sets of semi-structured data coming from various sources.

    Create Shell scripts to simplify the execution (Hbase, Hive, Oozie, Kafka and MapReduce) and move the data inside and outside of HDFS.

    Configure Sqoop and develop scripts to extract data from Teradata into HDFS.
    Develop multiple Kafka Producers and Consumers by Implementing data ingestion process and handle clusters in real time

    Test, build, design, deploy, and maintain the CICD process using tools like Jenkins, Maven Git, Docker and Enterprise Cloud Platform (eCP).

    Provide the daily progress in stand-up's, participate in the code reviews, work effectively with QA in creating test cases and deploy new releases in production

    .

    Requirements:


    The minimum education requirements to perform the above job duties are a Bachelor's degree in Computer Science, Applications or related technical field.

    Experience in Full lifecycle application development using Java/Databases - SQL and no SQL/Python technologies
    Proficiency in the Hadoop ecosystem - Hive, Hbase, HDFS, Oozie, Sqoop, pig, Spark, Kafka and other big data technologies.
    Excellent communication skills, ability to work well in a team in a fast paced environment

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