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The Senior AWS EMR Administrator will be responsible for managing AWS Elastic MapReduce (EMR) clusters and optimizing various AWS services. Candidates should have a strong background in big data technologies and AWS services, including Glue, Redshift, and Lambda. A bachelor's degree in Computer Science or a related field is required, along with at least 5 years of experience in AWS administration. Preferred certifications include AWS Certified Solutions Architect and AWS Certified Big Data – Specialty.
Job Responsibility:
Deploy, configure, and manage AWS EMR clusters, ensuring optimal performance and scalability
Install, configure, and maintain applications running on EMR clusters, such as Hadoop, Spark & Hive
Monitor cluster performance and resource utilization, implementing tuning strategies to optimize the performance and cost-efficiency of EMR clusters
Implement and manage backup and recovery processes for EMR data and configurations
Develop and maintain scripts for automating the deployment and management of EMR clusters and applications
Diagnose and resolve issues related to EMR clusters, applications, and data processing jobs
Work closely with data engineers, data scientists, and other stakeholders to support their big data processing needs
Administer and manage a variety of AWS services including AWS Glue, Amazon Redshift, AWS Lambda, Amazon S3, Amazon MSK (Kafka), KMS, and Secrets Manager to support data processing, storage, security, and compute needs
Implement AWS Step Functions to orchestrate workflows and integrate services like Lambda and Glue for end-to-end automation
Configure, manage, and optimize S3 buckets for efficient data storage, including setting up lifecycle policies and access controls
Optimize the performance and cost-effectiveness of AWS Lambda, Glue, and Redshift deployments through continuous monitoring and best practices
Automate infrastructure provisioning and management using Terraform
Leverage AWS CloudWatch to monitor performance metrics, set alarms, and implement automated responses to scaling events or failures
Work with development and data engineering teams to design and implement scalable data pipelines and analytics solutions using Redshift, Glue, and S3
Provide operational support for troubleshooting issues related to AWS services, performance bottlenecks, and data inconsistencies
Ensure high availability and reliability of critical systems through proactive monitoring, patching, and maintenance
Document architectural designs, configurations, and security policies to maintain a comprehensive knowledge base of the infrastructure
Stay up-to-date with the latest AWS developments and recommend improvements to systems, services, and workflows
Educate team members on AWS best practices for security, scalability, and cost optimization
Requirements:
Bachelor’s degree in computer science, Information Technology, or a related field
Proven experience with AWS services, particularly EMR, EC2, S3, and IAM
Strong background in administering big data technologies like Hadoop, Spark, Hive, and Presto
Experience with Linux/Unix systems administration
Experience with AWS services including Glue, Redshift, Lambda, Step Functions, S3, Kafka, KMS, Secrets Manager, IAM
Strong understanding of AWS security best practices, including managing IAM roles, KMS, Secrets Manager, and encryption standards
Experience with serverless architectures using AWS Lambda and Step Functions
Familiarity with data processing, ETL pipelines, and real-time data streaming using AWS Glue and MSK (Kafka)
Experience with infrastructure-as-code tools such as Terraform is preferred
Strong knowledge of AWS networking concepts, security protocols, and best practices
Proficiency in scripting languages such as Python, Shell, for automation tasks
Hands-on experience with monitoring tools like AWS CloudWatch and logging/alerting services
Good communication and collaboration skills to work with cross-functional teams
AWS Certified Solutions Architect, AWS Certified Big Data – Specialty, or other relevant certifications are a plus
Nice to have:
Understanding of data warehousing concepts and ETL processes
Knowledge of data security practices and compliance standards like GDPR and HIPAA