Who is happiest: Data Analysts, Scientists or Engineers?

Have you ever wondered which data professional is most satisfied with his/her job? What are the idiosyncrasies of them when it comes to looking for a new job or choosing one?

Photo by Brooke Cagle on Unsplash

Internet is full of content describing what data analysts, data scientists and data engineers do day-to-day in their jobs. However, not much is said about their difference from a more subjective perspective. If you’re looking for a change in careers and/or want to know how your preferences are aligned to theirs, keep on reading!

This post intends to answer three main questions regarding the idiosyncrasies of Data Analysts, Data Scientists and Data Engineers:

1. Which Data Professional is most satisfied with his/her job?
2. What are the main drivers each one looks for in a new job?
3. What are the most important factors each one considers in a job position?

The data is obtained from the 2020 Stack Overflow Annual Developer Survey, which contains nearly 65,000 responses fielded from over 180 countries and dependent territories. Of all the respondents, 10% of them work with data (data analyst, data scientist or machine learning specialist, and data engineer) with approximately the same proportion. The code used for the analysis is provided at the end of this post.

1. Which Data Professional is most satisfied with his/her job?

Participants were asked about their satisfaction with their career with the question:

How satisfied are you with your current job? (If you work multiple jobs, answer for the one you spend the most hours on.)

Results are shown in the Figure 1.

Figure 1: Which Data Professional is most satisfied with his/her job? Image by author

From the results shown in Figure 1, it’s clear that Data Scientists and Machine Learning Specialists are the ones most satisfied with their jobs. One might argue that this could be a consequence of their different salary. But, by looking at the data, Data Engineers have the highest compensation ($65k median), followed by Data Scientists ($55k median) and lastly by Data Analysts ($54k median) with a small margin.

Knowing that salary doesn’t have a big impact on job satisfaction, a natural question would be to ask what does, what people think does and what are they looking for in a new job.

2. What are the main drivers each one looks for in a new job?

Results are shown in Figure 2 to the question:

In general, what drives you to look for a new job? Select all that apply.

Figure 2: What are the main drivers each one looks for in a new job? Image by author

Unanimously, better compensation is the main driver for people working with data science (as it is overall for all respondents), although it doesn’t play an important role in job satisfaction. Drivers below the fifth one are pretty similar to each one of them, which is why I omitted from Figure 1. The interesting part resides between the second and fourth drivers, which accurately represents aspects inherently present in each role.

Between growth or leadership opportunities, wanting to work with new technologies and curious about other opportunities:

• Data or Business Analysts value growth or leadership opportunities more. This might be a reflection of their aspirations in life, which tend to be more focused on the business aspects of problems and eventually embracing management positions. It should be noted however that the three drivers differ by a small percentage.
• Data Scientists or Machine Learning Specialists are mostly driven in a new job because they’re curious about other opportunities. Although this curiosity might include a broad range of aspects, it’s indeed an important characteristic expected from them. They tend to pose questions and hypothesis, test them with the available data and solve hard problems using different approaches and algorithms. It’s also worthwhile noting that they are the ones least driven by better compensation (66%) compared to their data colleagues and the average developer (who prioritize it 70% of the times).
• Data Engineers, on the other hand, are more passionate about working with new technologies. This trait is a reflection of their inclination towards the technical side of problems and using different tools to approach them in an elegant and optimized way. Growth or leadership opportunities comes last by a considerable percentage, which might be because this may lead them to become less hands-on in coding.

Then, after motivated for seeking a new job, what do they value most when deciding between them?

3. What are the most important factors each one considers in a job position?

Participants were asked:

Imagine that you are deciding between two job offers with the same compensation, benefits, and location. Of the following factors, which 3 are MOST important to you?

Results are shown in Figure 3.

Figure 3: What are the most important factors each one considers in a job position? Image by author

Opportunities for professional development figures in first place for Data/Business Analysts and Data Scientists/Machine Learning Specialists and comes in second place for Data Engineers. The latter values most, with a significant margin, languages, frameworks, and other technologies they’d be working with, a technical aspect of the job, which is consistent with their response in the previous question. This makes sense, since they tend to specialize in it, differently than most data analysts and data scientists.

Interesting enough Data and Business Analysts consider a flexible schedule significantly more than their counterparts.

Key Takeaways

That was a lot of information! Let’s summarize it with some key takeaways about each Data Professional:

1. Among them, Data Scientists and Machine Learning Specialists are the ones most satisfied with their jobs by a margin of 26% compared to the average developer surveyed. They are the least concerned with better compensation and are driven by curiosity.
2. Data and Business Analysts are the ones least satisfied with their jobs by 8% less than the average developer. They are primarily driven by growth and leadership opportunities when looking for a new job, while carefully valuing flexible schedules.
3. Despite having the highest compensation among Data Professionals, Data Engineers are only 8% more satisfied with their jobs than the average developer. They tend to specialize in technologies and are driven by experimenting with new ones.

Final Note

Even though a lot of the conclusions here were intuitive, there were some interesting differences to note between data analysts, data scientists and data engineers. I hope that this article was useful to you in understanding more about their stated preferences and aspirations, and how these are aligned to yours. With that in mind, I have some questions for you to think about.

Are you happy with your job?

Are your motivations aligned to those working in your field?

What other drivers and factors are important to you?

The code and full analysis with the supporting data can be found on my Github. The findings here are observational and one should be careful when interpreting them.

This was my first blog post ever. Any suggestions are welcome!