Description

Our client represents the connected world, offering innovative and customer-centric information technology experiences, enabling Enterprises, Associates, and Society to Rise™.

They are a USD 6 billion company with 163,000+ professionals across 90 countries, helping 1279 global customers, including Fortune 500 companies. They focus on leveraging next-generation technologies, including 5G, Blockchain, Metaverse, Quantum Computing, Cybersecurity, Artificial Intelligence, and more, on enabling end-to-end digital transformation for global customers.

Our client is one of the fastest-growing brands and among the top 7 IT service providers globally. Our client has consistently emerged as a leader in sustainability and is recognized amongst the '2021 Global 100 Most sustainable corporations in the World by Corporate Knights.

We are currently searching for a Spark EKS Engineer (AWS Big Data Platform):

Responsibilities

• Administer and scale multi-petabyte Spark EKS clusters and related services on AWS.
• Perform provisioning, capacity planning, monitoring, and management of Spark EKS platforms.
• Enhance the performance of applications and middleware running on the platform.
• Troubleshoot and resolve Spark-related issues from application teams and internal clusters.
• Implement and maintain Spark, Flink, and Trino infrastructure, including monitoring, tuning, and troubleshooting.
• Improve scalability, service reliability, capacity, and performance of clusters and applications.
• Triage production issues in collaboration with operations and engineering teams.
• Conduct ongoing maintenance for large-scale global deployments.
• Write automation code for managing Big Data clusters.
• Participate in on-call rotations.

Requirements

• 5+ years of experience managing large-scale, multi-tenant Spark production clusters (1000+ nodes).
• Strong expertise in AWS services, including EMR, S3, and EKS (AWS Administrator level or higher preferred).
• Hands-on experience with Hadoop and Spark ecosystems.
• Proficiency in Python for development and automation.
• Experience with configuration management and automation tools.
• Deep understanding of Spark ecosystem and troubleshooting techniques.
• Ability to analyze logs, debug issues, and formulate solutions.
• Strong organizational skills with a focus on building, improving, and delivering results.
• Excellent communication and collaboration skills across teams.

Desired

• AWS certification in EMR or EKS cluster management.
• Experience with Flink and Trino infrastructure.
• Tools-first mindset with a focus on building tools to improve efficiency.

Education:

• Bachelor's or Master's degree in Computer Science or a related technical field.

Languages

• Advanced Oral English.
• Native Spanish.

Note:

• Fully remote
• Location Mostly remote but need to be in any of the City (GDL, Monterrey, MX City)

If you meet these qualifications and are pursuing new challenges, Start your application to join an award-winning employer. Explore all our job openings | Sequoia Career's Page: https://www.sequoia-connect.com/careers/.

Requirements

Responsibilities

• Administer and scale multi-petabyte Spark EKS clusters and related services on AWS.
• Perform provisioning, capacity planning, monitoring, and management of Spark EKS platforms.
• Enhance the performance of applications and middleware running on the platform.
• Troubleshoot and resolve Spark-related issues from application teams and internal clusters.
• Implement and maintain Spark, Flink, and Trino infrastructure, including monitoring, tuning, and troubleshooting.
• Improve scalability, service reliability, capacity, and performance of clusters and applications.
• Triage production issues in collaboration with operations and engineering teams.
• Conduct ongoing maintenance for large-scale global deployments.
• Write automation code for managing Big Data clusters.
• Participate in on-call rotations.