What are the responsibilities and job description for the AWS Infrastructure Engineer position at Heitmeyer Consulting?
Summary:
We are looking for a skilled Platform Engineer to join our Platform team, supporting and advancing our Data Science platform. This role focuses on building, maintaining, and scaling infrastructure that empowers Data Science and AI/ML teams.
Key Responsibilities:
We are looking for a skilled Platform Engineer to join our Platform team, supporting and advancing our Data Science platform. This role focuses on building, maintaining, and scaling infrastructure that empowers Data Science and AI/ML teams.
Key Responsibilities:
- Maintain and support ongoing Data Science infrastructure operations.
- Design, build, and deploy AWS environments using CI/CD pipelines to support a growing Data Science organization.
- Manage and scale platform environments to meet evolving business and technical needs.
- Own and enhance the image management lifecycle, ensuring consistency and reliability across environments.
- Set up and manage AWS accounts dedicated to Data Science workloads.
- Develop and maintain CI/CD pipelines using tools such as Azure DevOps.
- Implement and manage infrastructure using Infrastructure as Code (IaC) tools like Terraform.
- Write and maintain scripts and applications, primarily using Python.
- Administer and support databases including Athena, Oracle, MySQL, and PostgreSQL.
- Leverage AWS services to support Data Lake, Data Science, and AI/ML initiatives.
- Troubleshoot and resolve issues raised by development and business teams.
- Enforce infrastructure security, including guardrails, policies, and compliance controls.
- Address vulnerabilities within defined SLAs and maintain audit logs.
- Perform system upgrades, patching, and provide on-call support as needed.
- Conduct root cause analysis and share findings with internal teams.
- Collaborate with cross-functional teams including Network, Database, Infrastructure, and Architecture.
- Bachelor’s degree in Computer Science or a related discipline.
- 2 years of experience supporting Data Science infrastructure.
- 2 years of hands-on experience with AWS-based Data Lake, Data Science, and AI/ML services.
- Working knowledge (2 years) of:
- Kubernetes
- AWS services (e.g., SageMaker, Glue, Lambda, Athena)
- CI/CD tools such as Azure DevOps
- Infrastructure as Code tools such as Terraform
- Containerization technologies including Docker and ECR
- Security tools such as Aqua and Kenna
- Experience producing technical documentation and write-ups.
- AWS and/or Terraform certifications; Kubernetes certification (e.g., CKA) is a plus.
- Familiarity with service management practices and product lifecycle management.
- Proficiency in Python and shell scripting.
- Strong knowledge of database systems such as Athena, Oracle, and MySQL.
- Advanced experience with CI/CD and IaC tools, particularly Azure DevOps and Terraform.