Sr Hadoop Administrator

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Job Title : Sr Hadoop Admin, Data Platform
Job Summary:

We are seeking a highly skilled and experienced Sr. Hadoop Administrator to join our dynamic data engineering team. The ideal candidate will be responsible for the installation, configuration, maintenance, and performance optimization

of our Hadoop clusters and related big data technologies. You will play a critical role in ensuring the reliability, scalability, and security of our data platform, supporting our growing data analytics and business intelligence needs. This role requires strong technical expertise in Hadoop administration, excellent problem-solving skills, and the ability to collaborate effectively with cross-functional teams.

Responsibilities:

Install, configure, and maintain Hadoop clusters and related ecosystem components (e.g., HDFS, MapReduce, YARN, Hive, Pig, Spark, HBase, Kafka, ZooKeeper).
Monitor system performance, identify bottlenecks, and implement optimizations to ensure optimal efficiency and stability.
Perform capacity planning, resource allocation, and scaling of Hadoop clusters to meet growing data demands.
Implement and maintain security measures for Hadoop environments, including user access control, data encryption, and vulnerability management.
Troubleshoot and resolve complex issues related to Hadoop infrastructure and applications.
Develop and maintain scripts and automation tools for routine administrative tasks.
Collaborate with data engineers, data scientists, and application developers to understand their requirements and provide support for their big data initiatives.
Implement and manage backup and recovery strategies for Hadoop data and metadata.
Stay up-to-date with the latest Hadoop and big data technologies and best practices.
Document system configurations, operational procedures, and troubleshooting steps.
Participate in on-call rotation to provide support for critical production systems.
Contribute to the design and architecture of our evolving data platform.

Required Technical Skill Sets:
Operating Systems: Strong proficiency in Linux operating systems (e.g., CentOS, Red Hat, Ubuntu).
Hadoop Administration: Deep understanding and hands-on experience in administering and managing large-scale Hadoop clusters (Cloudera, Hortonworks, or Apache distributions).
Hadoop Ecosystem: Extensive knowledge of various Hadoop ecosystem components, including:
HDFS: Architecture, configuration, and management.
YARN: Resource management and job scheduling.
MapReduce: Understanding of the processing framework.
Hive: Data warehousing and SQL-like querying.
Spark: In-memory data processing and analytics.
HBase: NoSQL database integration.
Kafka: Distributed streaming platform.
ZooKeeper: Distributed coordination service.
Scripting and Automation: Proficiency in scripting languages such as Shell scripting (Bash), Python, or Perl for automation of administrative tasks.
Networking: Solid understanding of network concepts relevant to distributed systems.
Security: Experience implementing and managing security in Hadoop environments (Kerberos, Ranger, Sentry).
Monitoring and Logging: Experience with monitoring tools (e.g., Nagios, Ganglia, Cloudera Manager, Ambari) and log management systems (e.g., Splunk, ELK stack).
Troubleshooting: Excellent analytical and problem-solving skills to diagnose and resolve complex Hadoop issues.
Version Control: Familiarity with version control systems like Git.

Required Certifications:
While specific certifications are a plus, a strong understanding and proven experience in Hadoop administration are paramount. However, the following certifications are highly desirable:
Cloudera Certified Administrator for Apache Hadoop (CCAH)
Hortonworks Certified Apache Hadoop Administrator (HCA)
MapR Certified Hadoop Administrator (MCHA) (Note: MapR is now part of HPE Ezmeral)
Nice-to-Have Skills:

Cloud Platforms (Azure): Experience with Azure cloud services, particularly those related to data and analytics.
Azure Data Factory (ADF): Experience in designing, building, and deploying ETL/ELT pipelines using Azure Data Factory.
Databricks: Experience with the Databricks Unified Analytics Platform, including Spark optimization and cluster management.
Snowflake: Experience with the Snowflake cloud data warehouse platform.
Experience with containerization technologies like Docker and orchestration tools like Kubernetes.
Knowledge of data governance and data quality principles.
Experience with other NoSQL databases (e.g., MongoDB, Cassandra).
Familiarity with agile development methodologies.

Education and Experience:
Bachelor's degree in Computer Science, Information Technology, or a related field.
Minimum of 7 years of experience in administering and managing large-scale Hadoop environments.

Personal Attributes:
Strong communication and collaboration skills.
Ability to work independently and as part of a team.
Proactive and detail-oriented with a strong sense of ownership.
Ability to learn and adapt to new technologies quickly.
Excellent problem-solving and analytical skills.

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