Job
Description
Hadoop Administrator: Job Description: As an Open Source Hadoop Administrator, role will involve managing and maintaining the Hadoop infrastructure based on open source technologies within an organization. You will be responsible for the installation, configuration, and administration of open source Hadoop clusters and related tools in a production environment. Primary goal will be to ensure the smooth functioning of the Hadoop ecosystem and support the data processing and analytics needs of the organization. Responsibilities: Hadoop Cluster Management: Install, manual configure, and maintain open source Hadoop clusters and related components such as HDFS, YARN, MapReduce, Hive, Pig, Spark, HBase, etc. Monitor cluster health and performance, troubleshoot issues, and optimize cluster resources. Capacity Planning: Collaborate with data architects and infrastructure teams to estimate and plan for future capacity requirements of the open source Hadoop infrastructure. Scale the cluster up or down based on the changing needs of the organization. Security and Authentication: Implement and manage security measures for the open source Hadoop environment, including user authentication, authorization, and data encryption. Ensure compliance with security policies and best practices. Backup and Recovery: Design and implement backup and disaster recovery strategies for the open source Hadoop ecosystem. Regularly perform backups and test recovery procedures to ensure data integrity and availability. Performance Tuning: Monitor and analyze the performance of open source Hadoop clusters and individual components. Identify and resolve performance bottlenecks, optimize configurations, and fine-tune parameters to achieve optimal performance. Monitoring and Logging: Set up monitoring tools and alerts to proactively identify and address issues in the open source Hadoop environment. Monitor resource utilization, system logs, and cluster metrics to ensure reliability and performance. Troubleshooting and Support: Respond to and resolve incidents and service requests related to the open source Hadoop infrastructure. Collaborate with developers, data scientists, and other stakeholders to troubleshoot and resolve issues in a timely manner. Documentation and Reporting: Maintain detailed documentation of open source Hadoop configurations, procedures, and troubleshooting guidelines. Generate regular reports on cluster performance, resource utilization, and capacity utilization. Requirements: Proven experience as a Hadoop Administrator or similar role with open source Hadoop distributions such as Apache Hadoop, Apache HBase, Apache Hive, Apache Spark, etc. Strong knowledge of open source Hadoop ecosystem components and related technologies. Experience with installation, configuration, and administration of open source Hadoop clusters. Proficiency in Linux/Unix operating systems and shell scripting. Familiarity with cluster management and resource allocation frameworks. Understanding of data management and processing concepts in distributed computing environments. Knowledge of security frameworks and best practices in open source Hadoop environments. Experience with performance tuning, troubleshooting, and optimization of open source Hadoop clusters. Strong problem-solving and analytical skills. Hadoop Developer: Job Responsibilities: A Hadoop developer is responsible for designing, developing, and maintaining Hadoop-based solutions for processing and analyzing large datasets. Their job description typically includes: 1. Data Ingestion: Collecting and importing data from various sources into the Hadoop ecosystem using tools like Apache Sqoop, Flume, or streaming APIs. 2. Data Transformation: Preprocessing and transforming raw data into a suitable format for analysis using technologies like Apache Hive, Apache Pig, or Spark. 3. Hadoop Ecosystem: Proficiency in working with components like HDFS (Hadoop Distributed File System), MapReduce, YARN, HBase, and others within the Hadoop ecosystem. 4. Programming: Strong coding skills in languages like Java, Python, or Scala for developing custom MapReduce or Spark applications. 5. Cluster Management: Setting up and maintaining Hadoop clusters, including tasks like configuring, monitoring, and troubleshooting. 6. Data Security: Implementing security measures to protect sensitive data within the Hadoop cluster. 7. Performance Tuning: Optimizing Hadoop jobs and queries for better performance and efficiency. 8. Data Analysis: Collaborating with data scientists and analysts to assist in data analysis, machine learning, and reporting. 9. Documentation: Maintaining clear documentation of Hadoop jobs, configurations, and processes. 10. Collaboration: Working closely with data engineers, administrators, and other stakeholders to ensure data pipelines and workflows are running smoothly. 11. Continuous Learning: Staying updated with the latest developments in the Hadoop ecosystem and big data technologies. 12. Problem Solving: Identifying and resolving issues related to data processing, performance, and scalability. Requirements for this role typically include a strong background in software development, knowledge of big data technologies, and proficiency in using Hadoop-related tools and languages. Additionally, good communication skills and the ability to work in a team are important for successful collaboration on data projects.
