• US Citizen

• Green Card

• EAD (OPT/CPT/GC/H4)

• H1B Work Permit

• Corp-Corp

• W2-Permanent

• W2-Contract

• Contract to Hire

• Consulting/Contract

• UG :- - Not Required

• PG :- - Not Required

• No of position :- ( 1 )

• Post :- 20th Mar 2024

Required Skills:  
  
Platform Engineering:  
•    Cluster Management:  
o    Expertise in design, implement, and maintain Hadoop clusters in large volume, including components such as HDFS, YARN, and MapReduce.  
o    Collaborate with data engineers and data scientists to understand data requirements and optimize data pipelines.  
•    Administration and Monitoring:  
o    Experience in administering and monitoring Hadoop clusters to ensure high availability, reliability, and performance.  
o    Experience in troubleshooting and resolving issues related to Hadoop infrastructure, data ingestion, data processing, and data storage.  
•    Security Implementation:  
o    Experience in Implementing and managing security measures within Hadoop clusters, including authentication, authorization, and encryption.  
•    Backup and Disaster Recovery:  
•    Collaborate with cross-functional teams to define and implement backup and disaster recovery strategies for Hadoop clusters.  
•    Performance Optimization:  
o    Experience in optimizing Hadoop performance through fine-tuning configurations, capacity planning, and implementing performance monitoring and tuning techniques.  
•    Automation and DevOps Collaboration:  
o    Work with DevOps teams to automate Hadoop infrastructure provisioning, deployment, and management processes.  
•    Technology Adoption and Recommendations:  
o    Stay up to date with the latest developments in the Hadoop ecosystem.  
o    Recommend and implement new technologies and tools that enhance the platform.  
•    Documentation:  
o    Experience in documenting Hadoop infrastructure configurations, processes, and best practices.  
•    Technical Support and Guidance:  
o    Provide technical guidance and support to other team members and stakeholders.  
   
Admin:  
•    User Interface Design:  
o    Relevant for designing interfaces for tools within the Hadoop ecosystem that provide self-service capabilities, such as Hadoop cluster management interfaces or job scheduling dashboards.  
•    Role-Based Access Control (RBAC):  
o    Important for controlling access to Hadoop clusters, ensuring that users have appropriate permissions to perform self-service tasks.  
•    Cluster Configuration Templates:  
o    Useful for maintaining consistent configurations across Hadoop clusters, ensuring that users follow best practices and guidelines.  
•    Resource Management:  
o    Important for optimizing resource utilization within Hadoop clusters, allowing users to manage resources dynamically based on their needs.  
•    Self-Service Provisioning:  
o    Pertinent for features that enable users to provision and manage nodes within Hadoop clusters independently.  
•    Monitoring and Alerts:  
o    Essential for monitoring the health and performance of Hadoop clusters, providing users with insights into their cluster's status.  
•    Automated Scaling:  
o    Relevant for automatically adjusting the size of Hadoop clusters based on workload demands.  
•    Job Scheduling and Prioritization:  
o    Important for managing data processing jobs within Hadoop clusters efficiently.  
•    Self-Service Data Ingestion:  
o    Applicable to features that facilitate users in ingesting data into Hadoop clusters independently.  
•    Query Optimization and Tuning Assistance:  
o    Relevant for providing users with tools or guidance to optimize and tune their queries when interacting with Hadoop-based data.  
•    Documentation and Training:  
o    Important for creating resources that help users understand how to use self-service features within the Hadoop ecosystem effectively.  
•    Data Access Control:  
o    Pertinent for controlling access to data stored within Hadoop clusters, ensuring proper data governance.  
•    Backup and Restore Functionality:  
o    Applicable to features that allow users to perform backup and restore operations for data stored within Hadoop clusters.  
•    Containerization and Orchestration:  
o    Relevant for deploying and managing applications within Hadoop clusters using containerization and orchestration tools.  
•    User Feedback Mechanism:  
o    Important for continuously improving self-service features based on user input and experience within the Hadoop ecosystem.  
•    Cost Monitoring and Optimization:  
o    Applicable to tools or features that help users monitor and optimize costs associated with their usage of Hadoop clusters.  
•    Compliance and Auditing:  
o    Relevant for ensuring compliance with organizational policies and auditing user activities within the Hadoop ecosystem.