IT Engineer IV

Think Consulting; Atlanta (GA); On-site; USD 120,000 - 180,000; Full time

Job summary

Think Consulting in Atlanta is seeking an IT Engineer IV to evolve enterprise analytics, ML, and data science platforms in AWS. You will design, build, and automate scalable cloud services, with a strong focus on SageMaker and platform modernization.

The role emphasizes Infrastructure as Code with Terraform, CI/CD with GitLab, security governance, FinOps, and collaboration with multiple teams to deliver reliable, cost‑efficient platforms.

Qualifications

• 10+ years in cloud/platform engineering, DevOps or related fields.
• Deep AWS experience and cloud-native patterns.
• Experience supporting enterprise ML and data science platforms incl AWS SageMaker.
• Advanced scripting with Python or Shell.
• Terraform IaC and CI/CD implementation.
• Strong cloud security, IAM, vulnerability remediation.
• Proven reliability, monitoring, and performance improvements.
• Experience with cost optimization and FinOps.
• Strong analytical, troubleshooting, and cross-functional collaboration.
• Excellent documentation and communication skills.

Responsibilities

• Design, develop, and implement enhancements across AWS‑based analytics, ML, and data science platforms with SageMaker focus.
• Build and maintain automation solutions for provisioning, administration, maintenance, and operations.
• Improve platform scalability, availability, observability, security, and performance.
• Troubleshoot complex platform issues, perform root cause analysis, and implement long‑term fixes.
• Develop IaC frameworks using Terraform and modern cloud engineering practices.
• Enhance CI/CD pipelines and deployment automation with GitLab and cloud‑native tooling.
• Strengthen identity management, access controls, integrations, and self‑service capabilities.
• Lead security and vulnerability remediation initiatives and compliance improvements.
• Drive cloud cost optimization and FinOps strategies for efficiency.
• Support platform modernization, including analytics and ML platforms like Domino Data Lab.
• Assist SAS Grid migration and decommissioning activities with issue resolution and migration support.
• Create reusable engineering frameworks, automation patterns, and runbooks.
• Collaborate with Cloud Engineering, DevOps, InfoSec, Analytics, and App Development teams.
• Facilitate knowledge transfer and operational continuity for critical platform functions.

Skills

AWS

Cloud-native architecture

Python

Shell

Terraform

CI/CD

SageMaker

FinOps

Security governance

Troubleshooting

Tools

Terraform

GitLab

SageMaker

Domino Data Lab

SAS Grid

Job description

Position Overview

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.

Key Responsibilities

• 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.

Required Qualifications

• 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.

Preferred Qualifications

• 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.

Engagement Objectives

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