Hey everyone! I'm a Python Test Automation Engineer with about 6 years of experience, and I'm at a crossroads in my career thinking about how to advance in the industry. I've been reflecting on my options and narrowed it down to three potential paths: 1) SDET, where I can delve deeper into QA Automation and still learn a lot, like load testing; 2) DevOps, leveraging my automation skills for CI/CD pipelines; or 3) becoming a Developer, which is what I'm currently leaning towards because I love solving problems and seeing my creations come to life. However, I'm concerned about the current Python landscape, which seems so dominated by AI, Data Science, and Machine Learning. While I appreciate these technologies, I prefer not to work in this space. I feel like avoiding it might limit my career opportunities. Do you all have any advice or insights on this? Am I missing something about the market as it stands?
5 Answers
Choosing to be a developer is a wise move for long-term security. As a developer, you're the one innovating and creating, unlike support roles that may fade with advancements in development. Just keep in mind that DevOps Engineers also face a rapidly changing toolkit and need to stay current with new technologies regularly.
You might want to consider the earning potential too. Both DevOps and Development roles tend to have higher salary expectations compared to QA. It really depends on whether you like maintaining systems (DevOps) or working on actual programming (Developer).
A lot of newcomers in Python focus heavily on Data Science, often forgetting to learn solid programming practices. If you delve into Data and AI, you'd likely stand out in that realm. Plus, some data analysis skills can also aid in testing and understanding test results better!
From my experience, the SDET and DevOps paths are often less competitive and in high demand. Many QA professionals have made this transition successfully and found themselves in elevated roles. You might want to consider that.
Thanks for your insights!
Probably should've phrased that better, haha!
Curious about how Python fits into DevOps? While tools like Kubernetes and Docker are key, Python serves as a great scripting language for automating tasks, managing workflows, etc. For instance, I was involved in a project that combined Python with tools for deploying VMs and automating product deployment. It proves to be very useful in a DevOps context!
Totally agree! DevOps requires constant learning, especially with the fast pace of tools like Kubernetes.