Data Engineer → DevOps Engineer

A realistic transition from Data Engineer to DevOps Engineer: transferable skills, the gaps to close, a step-by-step learning plan and alternative routes. Estimated skill overlap 19%. Difficulty: Hard.

Difficulty: Hard6 stepsDuration: 16 to 20 monthsOverlap: 19%

Transition from Data Engineer to DevOps Engineer.

Transferable skills

  • Python / Go scripting
  • Cloud (AWS/Azure/GCP)

Skills to learn

  • CI/CD pipelines
  • Linux
  • Docker
  • Kubernetes
  • Terraform
  • Observability

Step-by-step learning plan

  1. 1. Build on your Data Engineer experience

    2–4 weeks

    Leverage

    • Python / Go scripting
    • Cloud (AWS/Azure/GCP)

    Map transferable skills — Python / Go scripting, Cloud (AWS/Azure/GCP) — against what a DevOps Engineer needs.

  2. 2. Learn the core of the DevOps Engineer role

    6–10 weeks

    Learn

    • CI/CD pipelines
    • Docker
    • Git & branching strategies
    • Linux

    Technologies

    AnsibleGitLab CIGitHub Actions

    Cover the biggest gaps first: CI/CD pipelines, Docker, Git & branching strategies.

  3. 3. Master advanced DevOps Engineer skills

    6–10 weeks

    Learn

    • Terraform
    • Kubernetes
    • Observability
    • Security in pipelines

    Technologies

    JenkinsArgoCDHelm

    Handle the advanced topics: Terraform, Kubernetes, Observability.

  4. 4. Get productive with the DevOps Engineer toolchain

    4–8 weeks

    Technologies

    AnsibleGitLab CIGitHub ActionsJenkinsArgoCDHelmAzurePrometheus

    Be hands-on with Ansible, GitLab CI, GitHub Actions and the rest of the target stack.

  5. 5. Practise DevOps Engineer work in real conditions

    4–8 weeks

    Ship a portfolio project or take on DevOps Engineer tasks at work.

  6. 6. Get certified and position yourself as a DevOps Engineer

    4–8 weeks

    Technologies

    CKAHashiCorp Terraform AssociateAWS DevOps Engineer Professional

    Update your CV and LinkedIn around DevOps Engineer, then apply to target roles.

Alternative routes