Python & Kubernetes Data Platform Engineer

Canonical; Dublin; On-site; EUR 60,000 - 85,000; Full time

Benefits offered by this job

Personal learning and development budget of USD 2,000 per year

Distributed work environment with team meet-ups

Annual compensation review

Job summary

Canonical is seeking Python and Kubernetes Specialist Engineers to build data solutions for public cloud infrastructure. You'll work with open-source machine learning tools and own solutions in the data analytics space. Join us in a fully distributed team where collaboration and innovation thrive.

Ideal candidates are passionate about technology, possess solid academic backgrounds, and have experience with Python and Kubernetes. We offer a supportive work environment, training budgets, and opportunities to collaborate globally.

Qualifications

• Exceptional academic track record from both high school and university.
• Confidence to respectfully speak up, exchange feedback, and share ideas.
• Passion for technology evidenced by personal projects.

Responsibilities

• Develop your understanding of the entire Linux stack.
• Design, build and maintain solutions on public and private clouds.
• Collaborate proactively with a distributed team.

Skills

Professional or academic software delivery using Python

Experience with Linux (Debian or Ubuntu preferred)

Hands-on experience with machine learning libraries

Experience with container technologies (Docker, LXD, Kubernetes)

Excellent interpersonal skills

Education

Undergraduate degree in a technical subject

Tools

Kubernetes

Python

Job description

Canonical is seeking Python and Kubernetes Specialist Engineers to build data solutions for public cloud infrastructure. You'll work with open-source machine learning tools and own solutions in the data analytics space. Join us in a fully distributed team where collaboration and innovation thrive.

Ideal candidates are passionate about technology, possess solid academic backgrounds, and have experience with Python and Kubernetes. We offer a supportive work environment, training budgets, and opportunities to collaborate globally.