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Cloud Ops Engineer

Roles & Responsibilities

  • 5+ years of experience in cloud operations, DevOps engineering, or related roles
  • Strong proficiency with at least one major cloud provider (AWS preferred)
  • Hands-on experience with infrastructure-as-code tools (Terraform, CloudFormation, or similar)
  • Strong scripting skills (Python, Bash, or PowerShell) and experience with CI/CD systems (GitHub Actions, Jenkins, CircleCI, GitLab CI)

Requirements:

  • Manage, scale, and optimize cloud environments for data science workloads (AWS, Azure, GCP) and orchestrate compute clusters (Kubernetes, ECS/EKS, Databricks, SageMaker) with high availability.
  • Develop CI/CD pipelines, infrastructure-as-code, and automated testing; build monitoring, alerting, and logging systems (e.g., CloudWatch, Prometheus, Grafana, ELK).
  • Ensure smooth data ingestion, transformation, and model execution workflows; provide reliable, reproducible environments for researchers; collaborate with Data Engineering for integration.
  • Implement data security, governance, risk assessments, patching, and compliance requirements for cloud operations; secure handling of sensitive data.

Job description

At Nimble Gravity we are looking for a Cloud Ops Engineer to join our team. The Cloud Operations Engineer will play a central role in the deployment, monitoring, and optimization of cloud platforms used by the Data Science team. This role requires hands-on expertise in cloud infrastructure (preferably AWS or Azure), modern DevOps practices, secure data operations, and automation frameworks. You’ll partner closely with data scientists, machine learning engineers, and data engineers to ensure our analytics systems run securely, efficiently, and at scale. 

 

Primary Responsibilities 

Cloud Infrastructure & Operations 

  • 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. 

DevOps & Automation 

  • 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. 

Data Platform Support 

  • 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. 

Security, Compliance & Governance 

  • 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. 

Cross-Functional Collaboration 

  • 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. 

 

Requirements 

Education & Certificates 

  • A bachelor’s degree or higher in a STEM field, required 

 

Professional Experience 

  • 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. 

 

Preferred 

  • Experience in financial services, investment management, or other highly regulated industries.
  • Knowledge of ML/AI platform tools (Databricks, SageMaker, MLflow, Airflow).
  • Understanding of networking, VPC architectures, and cloud security best practices.
  • Familiarity with distributed compute frameworks (Spark, Ray, Dask). 

 

About Nimble Gravity  

Nimble Gravity is a team of outdoor enthusiasts, adrenaline seekers, and experienced growth hackers. We love solving hard problems and believe the right data can transform and propel growth for any organization. 

Nimble Gravity is an Equal Opportunity Employer and considers applicants for employment without regard to race, color, religion, sex, orientation, national origin, age, disability, genetics or any other basis forbidden under federal, state, or local law. Nimble Gravity considers all qualified applicants. 

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