Quick Overview
Seniority
Mid Senior
Work mode
On Site
Location
Charlotte, NC, United States
Posted
22 hours ago
OracleSQLSVNShellETLTableauAnsibleHadoopHiveJavaJenkinsKafkaPerlPython
Job Description
Job Title: Hadoop Support with DevOps
Location: Plano, TX / Charlotte, NC (Onsite)
Job Type: Fulltime/Permanent
Experience: 10+ years
Must Have Technical/Functional Skills:
Primary Skill: Hadoop
Secondary: Linux, DevOps
Key Responsibilities:
- L1, L2 & L3 level support in Hadoop Platform
- Monitor and resolve HDFS and Ozone related issues.
- Investigate cluster performance, storage utilization, and capacity concerns.
- Manage quota requests, storage allocation, and capacity planning.
- Support platform maintenance and perform integration activities.
- Coordinate with application teams during incident and problem management.
- Create and maintain operational documentation, runbooks, and knowledge articles.
Required Qualifications:
- Experience on L1, L2 & L3 level support in Hadoop Platform.
- Experience in Yarn, Spark and Impala job debugging and troubleshooting.
- Experience in addressing issues around Name Node, HDFS Space, File/Folder Permission & backups.
- Understanding and experience in query performance tuning and resource utilization tuning.
- Technical knowledge on relational databases, data warehousing and SQL skills.
- Hadoop, Kafka, Spark, Impala, Hive, HBase, Ozone etc.
- Strong knowledge of Hadoop Architecture, HDFS, Hadoop Cluster and Hadoop Administrator’s role.
- Intimate knowledge of fully integrated AD/Kerberos authentication.
- Experience setting up optimum cluster configurations.
- Debugging knowledge of YARN.
- Hands-on with analyzing various Hadoop log files, compression, encoding, & file formats.
- Expert level knowledge of Cloudera Hadoop components such as HDFS, Sentry, HBase, Kafka, Impala, SOLR, Hue, Spark, Hive, YARN, Zookeeper and Postgres.
- Strong technical knowledge: Unix/Linux; Database (Sybase/SQL/Oracle), Java, Python, Perl, Shell scripting, Infrastructure.
- Experience in Monitoring & Alerting, and Job Scheduling Systems.
- Being comfortable with frequent, incremental code testing and deployment.
- Strong grasp of automation / DevOps tools - Ansible, Jenkins, SVN, Bitbucket.
Tools Involved:
- ETL tools: Hadoop Stack
- Job Scheduling tools: Autosys
- BI tools: Tableau; Tableau dashboard building connecting Hadoop-Hive Tables is equally preferred.
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