Job Summary
We are seeking an experienced Platform Engineer to join the Platform team responsible for managing the Data Science platform. This role will support Data Science infrastructure operations, develop and deploy AWS environments, manage large-scale infrastructure, and ensure secure, reliable, and scalable platform operations. The position is based in Columbus, OH or Dallas, TX and requires 4 days in office and 1 day remote.
Key Responsibilities
• Support ongoing Data Science infrastructure operations.
• Develop and deploy AWS environments using CI/CD processes for a rapidly growing team of Data Scientists.
• Manage and support large-scale environments to meet the needs of current and future Data Science teams.
• Champion and mature the environment by implementing and overseeing the image management lifecycle process.
• Assist in setting up and managing AWS accounts specifically for the Data Science platform.
• Provide hands-on development using CI/CD tools such as Azure DevOps.
• Utilize Infrastructure as Code (IaC) tools such as Terraform for environment setup and management.
• Develop scripts and applications using programming languages such as Python and shell scripting.
• Manage and support Kubernetes clusters and production environments.
• Manage database technologies including Athena, Oracle, MySQL, and PostgreSQL.
• Leverage AWS services essential for Data Lake, Data Science, and AI/ML teams, including Lambda, EC2, S3, Glue, SageMaker, and Athena.
• Handle and resolve requests from development and business users, addressing technical roadblocks.
• Manage secured infrastructure, enforce security measures, and apply necessary guardrails.
• Resolve infrastructure vulnerabilities within established SLAs and maintain audit logs.
• Perform system upgrades and patching and provide on-call support as needed.
• Conduct root cause analysis and knowledge transfer sessions with the internal team.
• Collaborate with Network, Database, Infrastructure, and Architecture teams to align on projects and strategies.
Required Qualifications
• Bachelor's degree in Computer Science or a related field.
• 2+ years of experience supporting Data Science Infrastructure.
• 2+ years of extensive experience with Data Lake, Data Science, and AI/ML services hosted on AWS infrastructure.
• 2+ years of working knowledge and hands-on experience with Kubernetes, including cluster management and production support.
• 2+ years of experience with AWS services such as SageMaker, Glue, Lambda, Athena, EC2, and S3.
• 2+ years of experience with CI/CD tools such as Azure DevOps.
• 2+ years of experience with Infrastructure as Code tools such as Terraform.
• 2+ years of experience with Docker and Amazon ECR (Elastic Container Registry).
• 2+ years of experience with security tools such as AQUA and Kenna.
• 2+ years of experience preparing technical write-ups and documentation.
• Strong experience supporting production Kubernetes clusters and troubleshooting infrastructure issues.
Preferred Qualifications
• AWS and Terraform certifications.
• Kubernetes certification such as CKA.
• Familiarity with technical service management and product lifecycle maintenance.
• Strong knowledge of programming and scripting languages such as Python and shell scripting.
• In-depth knowledge of database technologies including Athena, Oracle, MySQL, and PostgreSQL.
• Extensive experience with CI/CD and IaC tools such as Azure DevOps and Terraform.
Primary Skills
• AWS: Lambda, EC2, S3, Glue, SageMaker, Athena.
• Kubernetes and production cluster support.
• Terraform.
• Azure DevOps.
• Docker and Amazon ECR.
• Python and shell scripting.
• Data Lake, Data Science, and AI/ML infrastructure.
