Cloud - Platform Engineer

buscojobs España; Barcelona; Presencial; EUR 50.000 - 80.000; Jornada completa

Descripción de la vacante

A leading company in cloud services is seeking a Senior Platform Engineer to enhance their AWS infrastructure. This role involves designing scalable cloud solutions, optimizing CI/CD processes, and collaborating with various teams to ensure platform reliability and security. Ideal candidates will have significant experience with AWS and infrastructure as code tools like Terraform. This opportunity offers a dynamic work environment and a potential for impactful contributions to cloud initiatives.

Formación

• 5+ years of hands-on experience with AWS.
• Strong experience with Infrastructure as Code using Terraform.
• Proficiency in Docker and Kubernetes.

Responsabilidades

• Design and manage cloud infrastructure on AWS.
• Maintain CI/CD pipelines and automate deployments.
• Implement observability tools for monitoring.

Conocimientos

AWS Cloud Services

Terraform

CI/CD

Container Orchestration

Python

Linux System Administration

Monitoring

Scripting

Educación

Bachelor’s degree in Computer Science, Engineering, or related field

Herramientas

AWS CloudFormation

GitHub Actions

Jenkins

Prometheus

Grafana

ELK

Descripción del empleo

Job Type : Contract

We seek a skilled and proactive Senior Platform Engineer to design, build, and support scalable cloud infrastructure and automation pipelines on Amazon Web Services (AWS). You will work closely with DevOps, Security, Data, and AI Application teams to ensure platform reliability, security, and performance. Your role will be critical in driving infrastructure-as-code, CI / CD, observability, and cloud governance initiatives across the organization.

Key Responsibilities :

Design, implement, and manage cloud infrastructure on AWS using Infrastructure as Code (IaC) tools such as Terraform or AWS CloudFormation.

Maintain and enhance CI / CD pipelines using tools like GitHub Actions, AWS CodePipeline, Jenkins, or ArgoCD.

Ensure platform reliability, scalability, and high availability across development, staging, and production environments.

Automate operational tasks, environment provisioning, and deployments using scripting languages such as Python, Bash, or PowerShell.

Enable and maintain Amazon SageMaker environments for scalable ML model training, hosting, and pipelines.

Integrate AWS Bedrock to provide foundation model access for generative AI applications, ensuring security and cost control.

Manage and publish curated infrastructure templates through AWS Service Catalogue to enable consistent and compliant provisioning.

Collaborate with security and compliance teams to implement best practices around IAM, encryption, logging, monitoring, and cost optimization.

Implement and manage observability tools like Amazon CloudWatch, Prometheus / Grafana, or ELK for monitoring and alerting.

Support container orchestration environments using EKS (Kubernetes), ECS, or Fargate.

Contribute to incident response, post-mortems, and continuous improvement of the platform’s operational excellence.

Required Skills & Qualifications :

Bachelor’s degree in Computer Science, Engineering, or related field (or equivalent experience).

5+ years of hands-on experience with AWS cloud services.

Strong experience with Terraform, AWS CDK, or CloudFormation.

Proficiency in Linux system administration and networking fundamentals.

Solid understanding of IAM policies, VPC design, security groups, and encryption.

Experience with Docker and container orchestration using Kubernetes (EKS preferred).

Hands-on experience with CI / CD tools and version control (Git).

Experience with monitoring, logging, and alerting systems.

Strong troubleshooting skills and ability to work independently or in a team.

Preferred Qualifications (Nice to Have) :

AWS Certification (e.g., AWS Certified DevOps Engineer, Solutions Architect – Associate / Professional).

Experience with serverless technologies like AWS Lambda, Step Functions, and EventBridge.

Experience supporting machine learning or big data workloads on AWS