Platform Engineer - Data Science Infrastructure
Role details
Job location
Tech stack
Job description
STAFFXPERT LLC is seeking a Platform Engineer on behalf of our client in Columbus, OH, Dallas, TX, Tupelo, MS, and Minneapolis, MN., Support ongoing Data Science Infrastructure operations and platform stability. Develop, deploy, and manage AWS environments using CI/CD pipelines and Infrastructure as Code (IaC). Build and maintain scalable environments to support growing Data Science and AI/ML teams. Manage image lifecycle processes and platform standardization initiatives. Configure and manage AWS accounts and cloud resources for Data Science platforms. Implement and maintain CI/CD workflows using Azure DevOps or similar tools. Develop and maintain infrastructure automation using Terraform. Create scripts and automation tools using Python and shell scripting. Manage and support database technologies including Athena, Oracle, MySQL, and PostgreSQL. Utilize AWS services supporting Data Lake, Data Science, and AI/ML workloads, including SageMaker, Glue, Lambda, and Athena. Troubleshoot infrastructure issues, resolve vulnerabilities, and support secure cloud operations. Apply security controls, guardrails, patching, and audit logging practices across environments. Participate in root cause analysis, documentation, and knowledge transfer activities. Collaborate with cross-functional teams including Networking, Database, Infrastructure, and Architecture teams. Provide on-call support and assist with system upgrades and maintenance activities as needed.
Requirements
We are looking for both junior and senior-level professionals with strong experience in Data Science Infrastructure and cloud platform engineering. This role will support and enhance enterprise-scale Data Science and AI/ML environments hosted on AWS. The ideal candidate will have hands-on expertise in cloud infrastructure, CI/CD automation, Kubernetes, Terraform, and AWS Data Science services., Bachelor's degree in Computer Science, Information Technology, or a related field. 2+ years of experience supporting Data Science Infrastructure environments. 2+ years of hands-on experience with AWS-based Data Lake, AI/ML, and Data Science platforms. Strong experience with Kubernetes and containerized environments. Hands-on expertise with AWS services such as SageMaker, Glue, Lambda, Athena, and ECR. Experience with CI/CD tools such as Azure DevOps. Experience with Infrastructure as Code tools such as Terraform. Proficiency with Docker and container management. Experience working with security and vulnerability management tools. Knowledge of scripting/programming languages such as Python and Shell scripting. Experience with technical documentation and operational procedures. Strong troubleshooting, communication, and collaboration skills. Preferred Qualifications AWS, Terraform, Kubernetes, or CKA certifications preferred. Familiarity with technical service management and product lifecycle maintenance. Advanced knowledge of cloud security and infrastructure best practices. Experience managing enterprise-scale AWS infrastructure environments. Strong understanding of database technologies including Oracle, MySQL, PostgreSQL, and Athena.