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Job Description :-
The Senior Engineer is a hybrid role with experiences in database management, clustered compute, operating system integration, cloud concepts, storage solutions, application processing, and advanced monitoring techniques. The resource is usually having experience in multiple disciplines including Cloud, Linux as well as Hadoop. Must be able to lead complex projects and competing priorities with a high level of technical acumen and strong communication skills.
Required Skills:
- Experience with multiple large-scale Enterprise Hadoop or Big Data, Data Bricks, Cloudera, HD Insights, or other environments focused on operations, design, capacity planning, cluster setup, security, performance tuning, and monitoring.
- Experience with the full Cloudera CDH/CDP distribution to install, configure and monitor all services in the Cloudera stack.
- Strong understanding of core Hadoop services such as HDFS, MapReduce, Kafka, Spark and Spark-Streaming, Hive, Impala, HBase, Kudu, Sqoop, and Oozie
- Experience in administering, and supporting RHEL Linux operating systems, databases, and hardware in an enterprise environment.
- Expertise in typical system administration and programming skills such as storage capacity management, debugging, and performance tuning.
- Proficient in shell scripting (e.g., Bash, KSH, etc)
- Experience in setup, configuration, and management of security for Hadoop clusters using Kerberos with integration with LDAP/AD at an Enterprise level.
- Experience with large enterprise scale, separation of resource concepts, and the physical nature for those environments to operate (storage, memory, network, and compute)
Desired Skills:
- Certifications in one or many disciplines of Cloudera Hadoop, Cloud (Azure, AWS, Google), or RHEL
- Experience in version control systems (Git)
- Experience with Spectrum Conductor or Databricks with Apache Spark
- Experience in different programming languages (Python, Java, R)
- Enterprise Database Administration Platform Experience
- Experience In Large Analytic Tools including SAS, Search, Machine Learning, Log Aggregation
- Experience with Hadoop distributions in the Cloud is a plus, AWS, Azure, Google
