Data Technician Apprentice: IT Infra & Automation

Siemens Energy; Brande; On-site; DKK 156,000 - 223,000; Full time

Benefits offered by this job

Employer-funded pension

Personal and professional development

Job summary

Siemens Gamesa's Platform Engineering team is seeking a Data Technician Apprentice to help build and maintain enterprise software platforms powering wind farms worldwide. You will automate server provisioning, manage Linux and Windows servers, and develop Python automation scripts to enhance our operations.

You will gain hands-on experience with VMware infrastructure, collaboration across platform teams, and exposure to modern IT operations and delivery pipelines in a renewable energy context.

Qualifications

• Solid technical foundation in IT infrastructure and an interest in platform engineering.
• Experience with Linux, Python, virtualization, automation, or networking from projects.
• Analytical mindset and a structured approach to problem-solving.
• Willingness to learn new technologies and best practices.
• Good communication and teamwork within a team environment.

Responsibilities

• Automate server provisioning and configuration using Ansible.
• Configure, maintain, and troubleshoot Windows and Linux servers.
• Develop automation scripts and tools in Python.
• Support and maintain VMware-based virtual infrastructure.
• Collaborate with internal platform teams to automate software deliveries.

Skills

Linux

Python

Automation

Virtualization

Networking

Communication skills

Team collaboration

Tools

VMware

Job description

Siemens Gamesa's Platform Engineering team is seeking a Data Technician Apprentice to help build and maintain enterprise software platforms powering wind farms worldwide. You will automate server provisioning, manage Linux and Windows servers, and develop Python automation scripts to enhance our operations.

You will gain hands-on experience with VMware infrastructure, collaboration across platform teams, and exposure to modern IT operations and delivery pipelines in a renewable energy context.