Case Study: Upskilling as a Jobseeker in the Data Industry

As a job seeker, I have had numerous conversations with individuals who have successfully landed positions in organizations that not only align with their values but also push them to enhance their technical expertise. In one such enlightening conversation, I received valuable advice to consider pursuing certifications such as Azure, GCP, or AWS to validate my technical proficiency and knowledge.

However, I find that job searching is a time-consuming activity itself, and to add to it the task of preparing for an exam would require me to take away from job searching time. I was curious to find out if there’s truly a demand for certifications in the professions I’m interested in, so I created a system to support my deliberation.

I created a Python script that searches LinkedIn jobs in Canada for four specific job titles: data analyst, data scientist, data engineer, and Python developer. I have added my code as well as exploratory data analysis to this GitHub repo and saved the Tableau dashboard on the public server here. This is a quick overview of my findings:
➡️ I fetched a total of 495 job descriptions, out of which each job title had about a quarter portion as shown in the pie chart
➡️ Data Engineer roles have the highest demand for certifications at 34%, compared to the rest
➡️ Data Analyst and Data Scientist roles have about the same demand for certifications, around 16-17%
➡️ About a quarter of the Python Developer roles mention certifications in the job description

Based on the above, up to a third of the roles I’m interested in would be valued if I were to get a certification. I am encouraged by my findings to pursue a certification suited for a beginner, which one would you suggest?