IT Engineer IV

The Analytics Center of Excellence (CoE) is seeking a highly skilled IT Engineer IV to help drive the evolution of enterprise analytics, machine learning, and data science platforms. This role will provide hands-on engineering expertise focused on AWS cloud environments, platform automation, infrastructure modernization, and operational excellence.

The ideal candidate will possess deep experience with AWS-native services, platform engineering, and automation, with a strong emphasis on supporting and enhancing AWS SageMaker and enterprise data science environments. This individual will play a critical role in improving platform scalability, security, reliability, developer productivity, and cost efficiency while helping accelerate cloud modernization initiatives.

• Design, develop, and implement enhancements across AWS-based analytics, machine learning, and data science platforms, with a strong focus on AWS SageMaker.
• Build and maintain automation solutions that streamline platform provisioning, administration, maintenance, and operational support.
• Improve platform scalability, availability, observability, security, and overall system performance.
• Troubleshoot complex platform and infrastructure issues, perform root cause analysis, and implement long-term engineering solutions.
• Develop and maintain Infrastructure as Code (IaC) frameworks using Terraform and modern cloud engineering practices.
• Enhance CI/CD pipelines and deployment automation leveraging GitLab and cloud-native tooling.
• Strengthen platform identity management, access controls, integrations, and self-service capabilities.
• Lead security improvement initiatives, vulnerability remediation efforts, and compliance-focused engineering enhancements.
• Drive cloud cost optimization and FinOps initiatives to improve resource utilization and operational efficiency.
• Support platform modernization efforts, including enterprise analytics and machine learning platforms such as Domino Data Lab.
• Assist with the final phases of SAS Grid migration and decommissioning activities, including issue resolution, migration support, and asset retirement.
• Create reusable engineering frameworks, automation patterns, technical documentation, and operational runbooks.
• Collaborate with Cloud Engineering, DevOps, Information Security, Analytics, and Application Development teams to deliver enterprise platform improvements.
• Facilitate knowledge transfer and operational continuity for critical platform engineering functions.

• 10 years of experience in cloud engineering, platform engineering, DevOps, infrastructure engineering, or related technical disciplines.
• Strong hands-on expertise with AWS services and cloud-native architecture patterns.
• Experience supporting enterprise machine learning and data science platforms, including AWS SageMaker or similar technologies.
• Advanced scripting and automation experience using Python, Shell, or comparable languages.
• Hands-on experience with Terraform, Infrastructure as Code, and CI/CD pipeline implementation.
• Strong understanding of cloud security, identity and access management, vulnerability remediation, and governance best practices.
• Proven experience improving platform reliability, monitoring, observability, and performance.
• Experience implementing cloud cost optimization and FinOps strategies.
• Strong analytical and troubleshooting skills with the ability to solve complex technical challenges.
• Excellent communication, documentation, and cross-functional collaboration skills.

• Experience with Domino Data Lab or similar enterprise machine learning and analytics platforms.
• Experience supporting Python-based data science, AI, and machine learning workloads.
• Expertise with GitLab CI/CD pipelines and automated deployment frameworks.
• Experience implementing developer productivity tools, AI-assisted development capabilities, or platform engineering best practices.
• Familiarity with platform modernization, migration programs, and legacy system decommissioning initiatives.
• Knowledge of vulnerability management, compliance, and cloud governance frameworks.
• Prior exposure to SAS environments and analytics platform migrations is a plus.

During this engagement, the consultant will:

• Increase engineering capacity across AWS SageMaker and enterprise data science platforms.
• Deliver automation and platform improvements that reduce manual operational effort.
• Resolve critical technical challenges through scalable engineering solutions.
• Enhance platform security, reliability, observability, and cost efficiency.
• Support the successful completion of remaining SAS Grid migration and retirement activities.
• Capture and transfer critical platform knowledge to ensure operational continuity.
• Establish reusable engineering standards, automation frameworks, and documentation that enable long-term platform success.

Equal Opportunity Employer, including disability and protected veteran status