getSummary
Written in English from the original postingThe role involves designing, building, and optimizing Hadoop-based data processing pipelines for reliable, scalable batch analytics. It includes HDFS storage design, MapReduce pipeline development, monitoring, and operational troubleshooting. Required experience includes Hadoop fundamentals, Hive or Pig, YARN, Kerberos, and Linux.
Job description
Company Description
Kanz is partnering with Kanz 123 to build an inclusive and just employment ecosystem. Therefore, we prioritize individuals coming from all walks of life.Company Name: Kanz 123
Job Description
Design, build, and optimize Hadoop-based data processing pipelines to ensure reliable, scalable, high-performance batch analytics.
Key Performance Indicators- Improve job runtime and throughput
- Design scalable HDFS data storage
- Develop efficient MapReduce pipelines
- Implement data reliability and monitoring
- Reduce operational incidents and recovery time
Qualifications
Required Qualifications- 5+ years building Hadoop data pipelines
- Strong HDFS and MapReduce fundamentals
- Hands-on experience with Hive or Pig
- Experience with YARN and cluster operations
- Familiarity with security (Kerberos) and permissions
- Experience with Hadoop monitoring tools such as Ambari or Cloudera Manager
- Strong Linux experience for troubleshooting and operational support
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