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AWS Devops Cloud Engineer (Remote)

Remote · South Korea Full-time

Marlabs, a global AI and Digital Solutions Consulting firm, delivers intelligent solutions across AI, data, analytics, and product engineering. Since 2000, we have partnered with some of the largest healthcare, life sciences, financial services, and government organizations worldwide. As we continue to expand our global footprint, we have an exciting opportunity for a highly skilled AWS DevOps Cloud Engineer to join our innovative and dynamic team. Location: Hybrid in Indianapolis, IN (3 days/week onsite) AWS DevOps Cloud Engineer | About You As an AWS DevOps Cloud Engineer, you are responsible for executing and supporting application deployments across AWS environments while ensuring reliable, automated, and scalable release processes. You will work closely with application, SRE, infrastructure, and data platform teams to support cloud operations, CI/CD automation, production stability, and analytics platforms. AWS DevOps Cloud Engineer | Day-to-Day

  • Execute and support application deployments across AWS environments, ensuring reliable and repeatable release processes.
  • Develop, maintain, and optimize CI/CD pipelines, deployment automation, and Infrastructure as Code (Terraform, CloudFormation, CDK).
  • Support and troubleshoot AWS cloud infrastructure, application deployments, and production issues, serving as an escalation point for complex incidents.
  • Manage and support cloud-based data and analytics platforms, including Databricks, Amazon RDS, Redshift, and data lake environments.
  • Monitor platform health, performance, security, and operational stability while driving continuous improvements and automation.

AWS DevOps Cloud Engineer | Skills & Experience

  • Hands-on experience with AWS services including EKS, ECR, EC2, Lambda, S3, IAM, VPC, Route53, and RDS.
  • Experience building and supporting CI/CD pipelines and deployment automation.
  • Strong knowledge of Infrastructure as Code (Terraform, CloudFormation, and/or CDK).
  • Experience with container technologies such as Docker, Kubernetes, ECS, and EKS.
  • Experience supporting Databricks, Spark, data lake, Redshift, or other cloud-based analytics platforms.
  • Strong production support, troubleshooting, and scripting skills using Python, Bash, or similar technologies.

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