Happiest Jobs in Tech – anytime I’m asked what kind of work I do, I usually default to the “tech” response unless it’s someone in tech I’m speaking with. It is always assumed that the work I do is “cool” and would make anyone “happy”. Personally, I agree – but it got me thinking this morning about “how happy” people in tech tend to be. A Samuel Pottinger does a pretty decent job in this piece on researching this by tech role using some Data Science. I wonder how my fellow Product Managers would feel about these results?
The technology sector sees some of the highest salaries but also some of the highest turnover rates . When investigating this competitive but high attrition ecosystem, discussion often turns to how job satisfaction differs by company and how retention varies between employers . However, the focus on company ignores the fact that tech houses not just a multitude of corporations but also a diversity of people with different priorities and relationships to their interconnected fields of work. Investigating how experience varies by discipline, the 2019 Stack Overflow Developer Survey can help contextualize job satisfaction through field of work, compensation, and other factors to reveal not just who is most highly compensated but also who is most satisfied and what helps them find happiness at work .
To start, satisfaction does vary between disciplines. More specifically, the data show a statistically significant difference between fields of work given number of people indicating they are satisfied with their job versus the number indicating dissatisfaction (p < 0.05). Consider a metric which divides the number of people who report being satisfied (slightly or very satisfied) by the number dissatisfied (slightly or very unsatisfied) with their job. Using that “satisfaction ratio” metric to rank the fields of work within the Stack Overflow Developer Survey, four groups dominate the top ten most satisfied: management (executives and, to a lesser extent, engineering management), science (including data science), reliability (SRE and DevOps), and academia (educator and researcher). The data also show that most of the “developer” roles sit around the median value of 3.0 and, below that, one finds designers, PM, sales / marketing, and analysts.
One might suspect that compensation could account for this disparity in fields of work and, indeed, those reporting satisfaction with their jobs saw significantly higher salaries than those reporting dissatisfaction (difference of ~$21k difference, p < 0.05). Even still, consider that compensation may not be fully capturing variation in satisfaction. Though it can be a troublesome metric, linear regression on median discipline compensation only “explains” about a third of the variance in discipline satisfaction ratio (R² = 0.29) . Looking closer at the data, one can begin to see the fields of work that challenge that important but complicated relationship. For example, academic researcher yields low compensation compared to an engineering manger but both still report fairly similar high satisfaction ratios. Likewise, engineering managers, data scientists, and SREs may see a notable difference in pay but not necessarily a huge difference in satisfaction. Of course, if one is looking to optimize satisfaction and pay, one may consider senior executive / VP, SRE, or engineering manager. Still, while money might help, it doesn’t always seem to buy added happiness.
If compensation may not fully explain satisfaction in this sample, what else might be important within the tech landscape? The Developer Survey asks respondents about factors that might influence their decision to take a job (“… deciding between two job offers with the same compensation, benefits, and location … which 3 are [most] important to you?”) and, interestingly, there is a statistically significant difference in the frequency with which factors are selected by different disciplines (p < 0.05). Notably, developers of various kinds (front end, back end, etc) rank “[l]anguages, frameworks, and other technologies [they would] be working with” at the top of their list whereas culture tops the lists of PM, engineering managers, sales / marketing, and data scientists / analysts. Interestingly, looking at high satisfaction disciplines, impact of one’s work for both scientists (including data science) and senior executives may matter more than usual. Regardless, like with compensation, this variable ranking of factors may imply that different types of people in tech are searching for different things from their jobs and many factors may be acting holistically to support satisfaction.