Career advice for aspiring data practitioners
If you're reading this, you've probably been considering a career change recently. I assume you want to study something somewhat similar to software engineering and database design. You can do this no matter what your background is: marketing, analytics, finance, etc. This story will help you find the fastest way to get into the data space. I did the same thing many years ago and have never regretted it since. The tech space, especially data, is full of wonders and perks. You can do magical things with files and numbers, not to mention remote working and huge benefits from big IT companies. In this story, I will try to summarize a set of skills and possible projects that can be accomplished within a few months. Imagine being ready for your first job interview after just a few months of active learning.
Any sufficiently advanced technology is indistinguishable from magic.
Why data engineering instead of data science?
Indeed, why not data analysis or data science? I think the answer lies in the nature of this role, which combines the most difficult parts of these worlds. To become a data engineer, you need to study software engineering and database design, machine learning (ML) models, and understand data modeling and business intelligence (BI) development.
According to DICE, data engineering is the fastest growing occupation. Hurry because they conducted a study that proves there is a gap.
While data scientist has long been considered the “hottest” job on the market, there now appears to be some shortage of data engineers. We can see that there is a great demand in this field. This includes experienced and highly qualified engineers as well as entry-level roles.
Data engineering has been one of the fastest growing careers in the UK over the past five years, ranking 13th on LinkedIn's list of most in-demand jobs for 2023. [1]. upon…