Spark, Scala - Hyderabad / Secunderabad, Telangana - Cognizant Technology Solutions India Pvt Ltd

    Cognizant Technology Solutions India Pvt Ltd
    Cognizant Technology Solutions India Pvt Ltd Hyderabad / Secunderabad, Telangana

    2 days ago

    Full time ₹700,000 - ₹2,200,000 (INR) per year *
    Description
    • Develop, test, and deploy data processing applications using Apache Spark and Scala.
    • Optimize and tune Spark applications for better performance on large-scale data sets.
    • Work with the Cloudera Hadoop ecosystem (e.g., HDFS, Hive, Impala, HBase, Kafka) to build data pipelines and storage solutions.
    • Collaborate with data scientists, business analysts, and other developers to understand data requirements and deliver solutions.
    • Design and implement high-performance data processing and analytics solutions.
    • Ensure data integrity, accuracy, and security across all processing tasks.
    • Troubleshoot and resolve performance issues in Spark, Cloudera, and related technologies.
    • Implement version control and CI/CD pipelines for Spark applications.

    Required Skills & Experience:

    • Minimum 8 years of experience in application development.
    • Strong hands on experience in Apache Spark, Scala, and Spark SQL for distributed data processing.
    • Hands-on experience with Cloudera Hadoop (CDH) components such as HDFS, Hive, Impala, HBase, Kafka, and Sqoop.
    • Familiarity with other Big Data technologies, including Apache Kafka, Flume, Oozie, and Nifi.
    • Experience building and optimizing ETL pipelines using Spark and working with structured and unstructured data.
    • Experience with SQL and NoSQL databases such as HBase, Hive, and PostgreSQL.
    • Knowledge of data warehousing concepts, dimensional modeling, and data lakes.
    • Ability to troubleshoot and optimize Spark and Cloudera platform performance.
    • Familiarity with version control tools like Git and CI/CD tools (e.g., Jenkins, GitLab).
    * This salary range is an estimation made by beBee
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