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Infrastructure Engineer / Google Cloud Platform / Kubernetes / Load Testing
Why This Role Stands Out
This hybrid role offers a fantastic opportunity to shape highly scalable infrastructure for a global technology leader, leveraging cutting-edge Google Cloud Platform, Kubernetes, and AI technologies. You'll thrive here if you're a proactive engineer eager to build robust testing environments and automate performance analysis, contributing significantly to a unified technology future. This contract-to-hire position is perfect for someone ready to expand their skills in a dynamic, collaborative setting.
Quick Overview
Seniority
Mid Senior
Work mode
Hybrid
Location
New York, NY, United States
Posted
4 days ago
DatadogGatlingGoogle CloudGrafanaJMeterKubernetesPrometheusTerraformk6
Job Description
A global technology organization is hiring an Infrastructure Engineer focused on Performance & Load Testing to support the consolidation of several major dining and restaurant technology platforms. This is a 6-month contract-to-hire opportunity with a strong preference for candidates who can work hybrid in New York City. Candidates based in Chicago may also be considered.
This engineer will help build highly scalable, reliable infrastructure as multiple dining solutions are brought together into a unified technology environment. The role combines Google Cloud Platform, Kubernetes, performance engineering, observability, and test automation, with opportunities to work with modern infrastructure and emerging AI technologies. It is ideal for someone who can do more than execute load tests and is comfortable building the environments, tooling, test data, and infrastructure required to make performance testing effective.
Required Skills & Experience
Tech Breakdown
#LI-CK2
This engineer will help build highly scalable, reliable infrastructure as multiple dining solutions are brought together into a unified technology environment. The role combines Google Cloud Platform, Kubernetes, performance engineering, observability, and test automation, with opportunities to work with modern infrastructure and emerging AI technologies. It is ideal for someone who can do more than execute load tests and is comfortable building the environments, tooling, test data, and infrastructure required to make performance testing effective.
Required Skills & Experience
- Strong hands-on experience with Google Cloud Platform (Google Cloud Platform)
- Advanced experience deploying, operating, and troubleshooting Kubernetes environments
- Experience with performance, scalability, and load testing for distributed applications
- Ability to build and configure performance testing environments
- Experience with test data setup, data seeding, and environment preparation
- Ability to execute, automate, and trigger performance/load tests
- Strong understanding of application and infrastructure observability
- Experience with monitoring platforms such as Grafana, Prometheus, and Datadog
- Experience analyzing infrastructure and application performance to identify bottlenecks
- Strong troubleshooting skills across cloud infrastructure, containers, and application environments
- Ability to work cross-functionally with engineering, infrastructure, and quality teams
- Experience supporting high-volume consumer or transaction-based applications
- Experience with performance testing tools such as k6, JMeter, Gatling, or Locust
- Infrastructure-as-Code and automation experience with tools such as Terraform
- Experience with CI/CD pipelines and integrating performance tests into automated workflows
- Understanding of Kubernetes capacity planning, autoscaling, resource utilization, and performance tuning
- Experience working within restaurant technology, hospitality, marketplace, or e-commerce environments
- Exposure to AI-enabled engineering tools or modern AI technologies
- Experience supporting platform consolidation, migration, or large-scale modernization initiatives
Tech Breakdown
- 35% Google Cloud Platform & Kubernetes Infrastructure
- 30% Performance & Load Testing
- 20% Observability & Performance Analysis
- 15% Test Environment Automation & Data Seeding
- 40% Building and maintaining scalable performance-testing environments
- 25% Executing and automating load/performance tests
- 20% Monitoring results and troubleshooting performance bottlenecks
- 15% Collaborating with infrastructure, application engineering, and quality teams
#LI-CK2
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