Thoughts About the 2019 Salary Survey’s New Questions


Our annual Data Professional Salary Survey is open now and closes this Sunday. We’re asking a few new questions this year (based on your feedback), and here’s what we’re seeing so far.

At how many companies have you held this job?

This one came about because folks were curious if job hopping paid off:

If you’re doing correlation at home, the next question you’d probably ask is, “How does experience play into this?” Go download the raw data (click File, Download) to find out. I’ll leave it to the data scientists to say for sure, but at first glance, it looks like it might pay to job hop every 3 years.

How many employees does your company have overall?

Do people who work for smaller or larger companies make more money?

I don’t think I’d read too much into the 1-5 employees category – just a low number of responses there. However, it’s interesting to see the salaries drop the larger the company becomes. (This is a question that might be interesting to correlate with other questions, like how much experience someone has.)

How many hours per week do you work, on average?

This is one where the analysts will need to bucket the results:

I’m not surprised that there’s a diminishing return as you get past 60 hours though – at that point, let’s be honest, you’re not doing your best work.

What is the population of the largest city within 20 miles of where you work?

Forgive the sloppy visualizations (not to mention using the averages rather than medians) – racing to crank this out in my spare time:

And yep, looks like it pays more to live in bigger cities. We’ll probably remove that question for next year (along with any others y’all decide aren’t really teaching you stuff) since the less questions we ask, the more likely folks are to fill out the survey.

Want to help? Fill out the survey now.

Your data helps everyone understand whether they’re being paid fairly or not, and the more results we get, the more confident you can be with your analysis. The survey closes Sunday.

Previous Post
20 Questions to Ask About Your Availability Group Design
Next Post
38 Blog Posts We Couldn’t Write in 2018

3 Comments. Leave new

  • Did you remove any outliers for your analysis, or did you do it across the entire data set when you pulled the data?

  • Supposedly I will will be getting a large pay increase in February sometime. So, I guess my pay will look a little lower this year! And will skew the results downwards.


Leave a Reply

Your email address will not be published. Required fields are marked *

Fill out this field
Fill out this field
Please enter a valid email address.