Data Engineer (Cloud Data Platform Engineer)

About the role

We are looking for a hands-on Cloud DataOps & MLOps Engineer to help build and operate a modern AWS-based monitoring and ML platform environment. This role will focus on: Setting up and managing Amazon SageMaker Implementing centralized monitoring and observability using Prometheus and Grafana Building logging and metrics pipelines across AWS applications and services Supporting cloud platform automation, operational monitoring and MLOps enablement The ideal candidate should have a strong cloud engineering foundation and practical experience operating enterprise AWS environments.

Responsibilities

• Design and implement AWS cloud infrastructure and operational platforms
• Configure and manage Amazon SageMaker environments
• Set up centralized monitoring, metrics and alerting using Prometheus and Grafana
• Build logging and observability pipelines across applications and AWS services
• Develop dashboards, alerts and operational monitoring standards
• Support platform automation using Infrastructure-as-Code and CI/CD pipelines
• Work closely with application, data and platform teams to improve reliability and operational visibility
• Troubleshoot production issues and optimize cloud platform performance
• Required Skills & Experience
• Mandatory
• Strong hands-on AWS cloud experience
• Good understanding of: IAM
• VPC
• EC2
• S3
• CloudWatch
• ECS / EKS
• Security and networking fundamentals
• Experience with: Prometheus
• Grafana
• Monitoring and observability platforms
• Centralized logging architectures
• Experience with Amazon SageMaker or MLOps platforms
• Experience with Terraform, CloudFormation or similar IaC tools
• Scripting experience in Python or Bash
• Experience supporting production cloud environments
• Preferred
• Kubernetes / EKS experience
• OpenTelemetry experience
• CI/CD pipeline implementation
• DataOps or platform engineering background
• AWS certifications
• Ideal Candidate
• We are looking for someone who is:
• Hands-on and technically strong
• Comfortable working in enterprise cloud environments
• Strong in troubleshooting and operational support
• Proactive and able to work independently
• Able to communicate effectively with technical and business stakeholders
• Technology Environment
• AWS | SageMaker | Prometheus | Grafana | CloudWatch | Terraform | Python | Kubernetes | Docker | CI/CD

Requirements

• Experience supporting AI/ML platforms
• Experience with enterprise observability frameworks
• Multi-account AWS environment experience
• FinOps or cloud governance exposure
• We are driven by our AEIOU beliefs-Adventure, Excellence, Integrity, Ownership, and Unity-and we seek individuals who embody these values in both their professional and personal lives. We are committed to our Impact: Valuing our clients, Growing our people, and Creating our future.
• Together, we make the extraordinary happen.
• Learn more about us at ncs.co and visit our LinkedIn career site.
• Scam Alert
• We are aware of fraudulent job offers and impersonations of NCS recruiters. Phishing emails using convincing-looking but fake addresses are also commonly used to trick you into thinking that they come from official NCS sources.

Additional Information

Senior Cloud DataOps & MLOps Engineer (AWS, SageMaker, Prometheus, Grafana)

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