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Data Science, Digital Transformation and eCommerce Strategy from experienced eCommerce and AI/ML experts
Cloud Ops Engineer
Location
Latin America
Posted
176 days ago
Salary
0
Seniority
Senior
Job Description
Cloud Ops Engineer
Nimble Gravity
• Manage, scale, and optimize cloud environments used for data science workloads (e.g., AWS, Azure, GCP). • Provision, maintain, and optimize compute clusters for ML workloads (e.g., Kubernetes, ECS/EKS, Databricks, SageMaker). • Implement and maintain high-availability solutions for mission-critical analytics platforms. • Develop CI/CD pipelines for model deployment, infrastructure-as-code (IaC), and automated testing. • Build monitoring, alerting, and logging systems for cloud and ML infrastructure (e.g., CloudWatch, Prometheus, Grafana, ELK). • Automate provisioning, configuration, and deployments using tools such as Terraform, CloudFormation, or Pulumi. • Ensure smooth data ingestion, transformation, and model execution workflows. • Support data scientists with reliable, reproducible environments for research and development. • Collaborate with Data Engineering to maintain seamless integration between data pipelines and cloud systems. • Implement data science security controls and compliance requirements for cloud operations. • Conduct periodic risk assessments, patching, and governance reviews. • Support secure handling of sensitive financial and portfolio company data. • Partner with data scientists, machine learning engineers, and data engineers to support data-driven initiatives. • Serve as a technical advisor on cloud architecture, performance optimization, and operational excellence.
Job Requirements
- A bachelor’s degree or higher in a STEM field, required
- 5+ years of experience in cloud operations, DevOps engineering, SRE, or related roles.
- Strong proficiency with at least one major cloud provider (AWS preferred).
- Hands-on experience with IaC tools (Terraform, CloudFormation, or similar).
- Strong scripting skills (Python, Bash, or PowerShell).
- Experience with CI/CD systems (GitHub Actions, Jenkins, CircleCI, GitLab CI).
- Familiarity with container orchestration (EKS, Kubernetes, ECS, AKS).
- Experience supporting data-intensive or ML workloads.
Benefits
- Competitive salary
- Flexible working hours
- Professional development budget
- Home office setup allowance
- Global team events
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