Job Description

Hadoop Admin

Charlotte, NC

Must Have: MapR/ Map-Reduce

Job Description & Responsibilities

• Responsible for implementation and ongoing administration of Hadoop infrastructure.
• Aligning with the systems engineering team to propose and deploy new hardware and software environments required for Hadoop and to expand existing environments.
• Working with data delivery teams to setup new Hadoop users. This job includes setting up Linux users, setting up Kerberos principals and testing HDFS, Hive and MapReduce access for the new users.
• General operational expertise such as good troubleshooting skills, understanding of system's capacity, bottlenecks, basics of memory, CPU, OS, storage, and networks
• Should be able to deploy Hadoop cluster, add and remove nodes, keep track of jobs, monitor critical parts of the cluster, configure name-node high availability, schedule and configure it and take backups
• Performance tuning of Hadoop clusters and Hadoop MapReduce routines.
• Screen Hadoop cluster job performances and capacity planning
• Monitor Hadoop cluster connectivity and security
• Manage and review Hadoop log files
• File system management and monitoring
• HDFS support and maintenance
• Diligently teaming with the infrastructure, network, database, application and business intelligence teams to guarantee high data quality and availability.
• Collaborating with application teams to install operating system and Hadoop updates, patches, version upgrades when required.
• Performance tuning of Hadoop clusters and Hadoop MapReduce routines

Preferred Job Qualifications

• Minimum 4-5 years of recent Hadoop Administration experience with strong knowledge of Hadoop Architecture(HDFS), Hadoop Cluster installation, configuration, monitoring, cluster security, cluster resources management, maintenance and performance tuning
• Previous experience as RDBMS DBA is a plus
• Knowledge of Hadoop components such as HDFS, Sentry, Kafka, Spark, Hive, YARN, Zookeeper.
• Strong knowledge of key scripting and programming languages such as Python, Scala, and Bash.
• Strong understanding and experience with Hadoop Stack including HDFS, Hive, HBase, Cassandra, Yarn, Scoop, oozie, Spark.
• Knowledge of relational and non-relational databases, industry practices, techniques, standards and sensitive, PII data handling.
• Proficient with system upgrades, patches, maintaining compliance, and support audits.