Good news: wages within the tech industry grew 2.3 percent year-over-year in the second quarter of 2019, according to new data from PayScale. 

That outpaced industries such as construction (which grew 2.2 percent y/y), healthcare (1.8 percent), manufacturing (1.6 percent), and energy & utilities (1.1 percent). Nor should this data come as a surprise: with tech-industry unemployment at notable lows, companies will obviously have to pay more for the specialized talent they need. According to a CompTIA analysis of U.S. Bureau of Labor Statistics (BLS) data, the current tech unemployment rate is 1.3 percent, a 20-year low.

It may also be a sign that tech wages are on an upswing after a period of stagnation. According to Dice’s data, average tech-professional salaries only increased 0.7 percent between 2017 and 2018, hitting $93,244. As we noted in this year’s Salary Survey, some 68 percent of tech professionals are interested in changing employers in order to receive higher compensation (well ahead of those who said they’d jump jobs for better working conditions or more responsibility).

In times of stagnant wages, many employers resort to non-salary perks and benefits in an effort to get employees to stick around. Some of these benefits are great for tech professionals’ careers—who wouldn’t want free education, for example? But some perks also miss the mark; it’s hard to get excited enough about free snacks and cold-brew coffee to stay at your current firm in the face of a better offer.

But if wages are climbing, employers may prove more inclined to dig deep into their budgets and come up with salary commensurate with what tech professionals are actually worth. That’s a good thing! However, employers aren’t going to just randomly make it rain $100 bills upon employees; they’re often in search of particular skill-sets, which is why it’s important for professionals to keep as current as possible with the technologies they use. It’s also vital to stay aware of industry trends, such as the current embrace of artificial intelligence (A.I.) and machine learning.