11/04/2026 updated

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DevOps Engineer / Platform Engineer / Cloud Architect / AWS GCP Azure Kubernetes Terraform

Paris, France
Only remote
M.Sc in computer science
Paris, France
Only remote
M.Sc in computer science

Profile attachments

Tarek-Cloud-Architect__ (1).pdf

About me

Senior DevOps and Cloud Architect expert in designing, building, and operating cloud infrastructure at scale across AWS, GCP, and Azure. I don't just manage infrastructure I engineer it from the ground up, treating it as a product that needs to be reliable, secure & maintainable.

Platform EngineeringAmazon Web ServicesAuditingAutomationBuild AutomationMicrosoft AzureCloud ComputingCloud EngineeringComputer NetworksDevOpsDistributed SystemsIdentity ManagementInfrastructure ManagementPython (Programming Language)Machine LearningRole-Based Access ControlAnsiblePrometheusSecurity ManagingSoftware VersioningWorkflowsDatadogMetricsCloud MonitoringGrafanaGitLabGitGitlab-ciKubernetesMachine Learning OperationsCloud MigrationTerraformDocker
  1. Design and deploy cloud infrastructure across AWS, GCP, and Azure — choosing the right provider and services based on workload requirements and cost efficiency
  2. Write and maintain all infrastructure as code using Terraform — modular, versioned, peer-reviewed, and fully repeatable across environments
  3. Build and manage Kubernetes clusters (EKS, GKE, AKS) — handling deployments, autoscaling, resource limits, ingress, and day-2 operations
  4. Set up and maintain CI/CD pipelines on GitLab CI — from code commit to production, fully automated with quality gates, tests, and rollback strategies
  5. Implement GitOps workflows using tools like ArgoCD or Flux — infrastructure and application state driven entirely from Git repositories
  6. Containerise applications with Docker and manage multi-environment deployments across dev, staging, and production
  7. Build and maintain MLOps pipelines — model training automation, versioning, serving infrastructure, and monitoring for machine learning workloads
  8. Manage secrets, access control, and identity across cloud providers — IAM, Workload Identity, RBAC, and secrets management solutions
  9. Monitor and observe everything — metrics, logs, and traces using Prometheus, Grafana, Loki, Datadog, or native cloud monitoring tools
  10. Enforce security best practices across all layers — network policies, least-privilege access, vulnerability scanning in pipelines, and compliance checks
  11. Optimise cloud costs continuously — rightsizing, spot/preemptible instances, reserved capacity planning, and usage auditing
  12. Collaborate with dev and data teams to standardise workflows, tooling, and deployment practices across the organisation
  13. Troubleshoot production incidents — reading logs, tracing failures across distributed systems, patching fast, and writing post-mortems

Experience

Professional experience10+ years
Freelancer since2014

Languages

GermanGoodEnglishNative speakerFrenchNative speakerItalianNative speaker

Project history

Cloud and DevOps Engineer Senior | AWS Kubernetes Terraform CI/CD

PICONSULTING
  1. Design and deploy cloud infrastructure across AWS, GCP, and Azure choosing the right provider and services based on workload requirements and cost efficiency
  2. Write and maintain all infrastructure as code using Terraform modular, versioned, peer-reviewed, and fully repeatable across environments
  3. Build and manage Kubernetes clusters (EKS, GKE, AKS) handling deployments, autoscaling, resource limits, ingress, and day-2 operations
  4. Set up and maintain CI/CD pipelines on GitLab CI from code commit to production, fully automated with quality gates, tests, and rollback strategies
  5. Implement GitOps workflows using tools like ArgoCD or Flux infrastructure and application state driven entirely from Git repositories
  6. Containerise applications with Docker and manage multi-environment deployments across dev, staging, and production
  7. Build and maintain MLOps pipelines model training automation, versioning, serving infrastructure, and monitoring for machine learning workloads
  8. Manage secrets, access control, and identity across cloud providers IAM, Workload Identity, RBAC, and secrets management solutions
  9. Monitor and observe everything metrics, logs, and traces using Prometheus, Grafana, Loki, Datadog, or native cloud monitoring tools
  10. Enforce Cloud security best practices across all layers
  11. Optimise cloud costs continuously
  12. Collaborate with dev and data teams to standardise workflows, tooling, and deployment practices
  13. Troubleshoot production incidents

Certificates

Certified Kubernetes Application Developer

Linux Foundation

2024

Terraform Associate

Hashicorp

2023

AWS Solutions Architect

AWS

2022

Portfolio

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