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- Tasks: Build innovative solutions using Python and Kubernetes for cloud infrastructure.
- Company: Leading open source tech firm with a focus on innovation.
- Benefits: Flexible remote work, competitive salary, and opportunities for professional growth.
- Why this job: Join a dynamic team and work with cutting-edge open-source tools.
- Qualifications: Strong Python skills, Kubernetes knowledge, and data analytics experience.
- Other info: Collaborative environment across time zones with exciting projects.
The predicted salary is between 28800 - 48000 £ per year.
A leading open source tech firm is seeking a Python and Kubernetes Specialist Engineer to build innovative solutions for public cloud and private infrastructure. Candidates should have strong Python skills, understanding of Kubernetes, and experience in data analytics. This role promotes a distributed work model, encouraging collaboration across time zones. Join a team working with state-of-the-art open-source tools in an innovative environment.
Data & AI/ML Engineer - Python + Kubernetes in Glasgow employer: Canonical
Contact Detail:
Canonical Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data & AI/ML Engineer - Python + Kubernetes in Glasgow
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, especially those who work with Python and Kubernetes. Join relevant online communities or forums where you can connect with potential employers and showcase your skills.
✨Tip Number 2
Show off your projects! If you've built anything cool using Python or Kubernetes, make sure to highlight it. Create a portfolio or GitHub repository to demonstrate your expertise and innovative solutions you've developed.
✨Tip Number 3
Prepare for technical interviews by brushing up on your coding skills and understanding of data analytics. Practice common interview questions related to Python and Kubernetes, and be ready to solve problems on the spot.
✨Tip Number 4
Don’t forget to apply through our website! We’ve got loads of opportunities that might just be the perfect fit for you. Plus, it’s a great way to get noticed by our hiring team directly.
We think you need these skills to ace Data & AI/ML Engineer - Python + Kubernetes in Glasgow
Some tips for your application 🫡
Show Off Your Python Skills: Make sure to highlight your Python expertise in your application. We want to see how you've used Python in real-world projects, so don’t hold back on the details!
Kubernetes Know-How: If you’ve got experience with Kubernetes, let us know! Share specific examples of how you’ve implemented it in your work. This will help us understand your hands-on experience.
Data Analytics Experience: Since this role involves data analytics, be sure to mention any relevant experience you have. We’re keen to see how you’ve tackled data challenges and what tools you’ve used.
Apply Through Our Website: We encourage you to apply through our website for a smoother process. It helps us keep track of applications and ensures you don’t miss out on any important updates!
How to prepare for a job interview at Canonical
✨Know Your Python Inside Out
Make sure you brush up on your Python skills before the interview. Be ready to discuss your experience with Python in detail, including any projects you've worked on. Practising coding challenges can also help you demonstrate your problem-solving abilities.
✨Get Familiar with Kubernetes
Since this role requires a solid understanding of Kubernetes, take some time to review its core concepts and functionalities. Be prepared to explain how you've used Kubernetes in past projects and how it can be leveraged for building scalable applications.
✨Showcase Your Data Analytics Experience
Highlight your experience in data analytics during the interview. Prepare examples of how you've used data to drive decisions or improve processes. This will show that you not only understand the technical side but also how to apply it effectively.
✨Embrace the Distributed Work Model
Since the company promotes a distributed work model, be ready to discuss how you manage collaboration across different time zones. Share any experiences you have working remotely and how you ensure effective communication and teamwork in such settings.
