Systems Engineering Associate — Cloud, Automation & ML

The Goldman Sachs Group; Town of Texas (WI); On-site; USD 95,000 - 140,000; Full time

Job summary

The Goldman Sachs Group, Inc. invites applications for an Associate, Systems Engineering in Dallas, TX. This role develops expertise across engineering domains, including datacenter design, networks, storage, compute, OS, databases, and software languages to deliver scalable, cloud-based infrastructure.

You will automate testing, monitoring, and deployment, apply data mining and machine learning to detect and respond to issues, and contribute to disaster recovery and performance tuning.

Qualifications

• Bachelor's degree in Computer Science, Computer Engineering, Information Systems/Technology, or related fields and two years of experience in performance tuning, troubleshooting, and SDLC involvement.
• Experience with Windows and UNIX operating systems, including shell scripting and log analysis.
• Experience with public Cloud providers (Azure, AWS) and developing Infrastructure as Code scripts for resource deployments.

Responsibilities

• Develop expertise across engineering domains including datacenter design, networks, storage, and databases.
• Design and build scalable, cloud-based infrastructure for on-demand application scaling.
• Automate testing processes, monitoring, and incident response to improve stability and performance.
• Assist in disaster recovery planning and change management; monitor production and analyze discrepancies.

Skills

Cloud platforms

Automation

Data analytics

Shell scripting

Education

Bachelor's degree in Computer Science or related field

Tools

Azure

AWS

IaC (Terraform/CloudFormation)

PowerShell

Job description

The Goldman Sachs Group, Inc. invites applications for an Associate, Systems Engineering in Dallas, TX. This role develops expertise across engineering domains, including datacenter design, networks, storage, compute, OS, databases, and software languages to deliver scalable, cloud-based infrastructure.

You will automate testing, monitoring, and deployment, apply data mining and machine learning to detect and respond to issues, and contribute to disaster recovery and performance tuning.