DataOps / Cloud DevOps Engineer - Senior - EY Global Delivery Services

EY; Buenos Aires; On-site; ARS 1,800,000 - 2,400,000; Full time

Job summary

EY GDS is actively recruiting a DataOps / Cloud DevOps Engineer to join our Cloud, Data & AI practice in Argentina. You will design, automate, and maintain scalable cloud environments and deployment frameworks that enable reliable delivery of business-critical solutions.

The role collaborates with architects, developers, and client stakeholders to accelerate cloud applications, analytics platforms, and AI solutions through IaC, CI/CD pipelines, Kubernetes, and observability across Azure and AWS

Qualifications

• 3–6 years of experience in DevOps, Cloud or DataOps roles.
• Bachelor's degree in CS, SE, IT or related field.
• Experience designing CI/CD pipelines with GitHub Actions, Azure DevOps, GitLab CI/CD or similar.
• Strong IaC experience with Terraform.
• Experience with AKS/EKS or other Kubernetes platforms.
• Scripting in Python, PowerShell, Bash or similar.
• Knowledge of cloud-native architectures and data platforms.
• Excellent communication and stakeholder management.
• Consulting mindset with ability to adapt to client environments.

Responsibilities

• Design, develop, and maintain CI/CD pipelines for cloud applications, data platforms, and AI solutions.
• Implement and manage IaC using Terraform and cloud-native services.
• Deploy, configure, and maintain enterprise cloud environments on Azure and/or AWS.
• Build and support Kubernetes-based platforms for containerized workloads and microservices.
• Automate deployments across development, testing, and production environments.
• Develop and maintain GitHub Actions workflows and deployment frameworks.
• Support CI/CD for Azure Functions, Web Apps, APIs, Kubernetes Services.
• Collaborate with solution architects, software developers, and data engineers to improve platform reliability and deployment efficiency.
• Implement monitoring, logging, alerting, and observability across cloud platforms.
• Support security, compliance, identity management, secrets management, and governance requirements.
• Contribute to reusable deployment templates and platform automation frameworks.
• Promote DevOps and DataOps best practices.

Skills

DevOps

Cloud engineering

Stakeholder management

Communication

Consulting mindset

Education

Bachelor's degree in Computer Science

Tools

GitHub Actions

Terraform

Azure DevOps

GitLab CI/CD

AKS

AWS EKS

Python scripting

Job description

Fecha: 12 sept 2026

EY GDS is actively recruiting a DataOps /Cloud DevOps Engineer to join our growing Cloud, Data & AI practice. We are looking for a technology professional with experience supporting enterprise cloud platforms, data ecosystems, and modern application delivery through automation, Infrastructure as Code, and DevOps best practices.

The successful candidate will work closely with solution architects, cloud engineers, data engineers, application developers, and client stakeholders to build, automate, and maintain scalable cloud environments and deployment frameworks that enable reliable delivery of business-critical solutions.

As a DataOps /Cloud DevOps Engineer at EY GDS, you will help accelerate the delivery of cloud applications, analytics platforms, and AI solutions by implementing Infrastructure as Code, CI/CD pipelines, container platforms, monitoring capabilities, and operational excellence practices across enterprise environments.

Responsibilities

• Design, develop, and maintain CI/CD pipelines supporting cloud applications, data platforms, and AI solutions.
• Implement and manage Infrastructure as Code (IaC) using Terraform and cloud-native services.
• Deploy, configure, and maintain enterprise cloud environments across Azure and/or AWS.
• Build and support Kubernetes-based platforms for containerized workloads and microservices.
• Automate application, infrastructure, and data platform deployments across development, testing, and production environments.
• Develop and maintain GitHub Actions workflows and deployment automation frameworks.
• Support ci/cd for cloud-native services including Azure Functions, Web Apps, APIs, Kubernetes Services, and other platform components.
• Collaborate with solution architects, software developers, and data engineering teams to improve platform reliability, scalability, and deployment efficiency.
• Implement monitoring, logging, alerting, and observability solutions across cloud platforms.
• Support security, compliance, identity management, secrets management, and governance requirements.
• Contribute to reusable deployment templates, engineering standards, and platform automation frameworks.
• Promote DevOps and DataOps best practices, including source control, automated testing, release management, and operational excellence.

Required experience

• 3 to 6 years of experience in DevOps, Cloud Engineering, Platform Engineering, DataOps, or related roles.
• Bachelor's degree in computer science, Software Engineering, Information Technology, Data Engineering, or a related field.
• Experience designing and maintaining CI/CD pipelines using GitHub Actions, Azure DevOps, GitLab CI/CD, or similar technologies.
• Strong experience with Infrastructure as Code and Terraform.
• Experience with Azure Kubernetes Service (AKS), Amazon EKS, or other Kubernetes platforms.
• Experience with scripting and automation using Python, PowerShell, Bash, or similar languages.
• Knowledge of cloud-native architectures and application hosting patterns.
• Familiarity with enterprise data platforms and modern analytics ecosystems.
• Understanding of cloud security, networking fundamentals, and operational best practices.
• Experience working with Azure and/or AWS cloud platforms.
• Excellent communication and stakeholder management skills.
• Consulting mindset with the ability to adapt to different client environments and technology stacks.

We are looking for passionate individuals who enjoy building and automating modern cloud platforms that power applications, data products, and AI solutions. If you are interested in Kubernetes, Infrastructure as Code, CI/CD automation, cloud-native services, and enabling engineering teams to deliver solutions faster and more reliably.