Pros
Good for entry level/college graduates to get some work experience. Warren Barkley, CTO is no longer with the company. Quicker escalation into management roles than other companies. Even if you need to wait for someone to move up or move out, you likely won't have to wait long. More interdepartmental transfers allowed than I have seen at other companies. My final compensation was only slightly less than market for my background, but it took a lot of self-advocating to get there, and I was taking on a LOT more responsibility than my peers making the same or more than me at other Boise companies. Decent benefits.
Cons
The culture, work/life balance, and ability to take meaningful vacation have deteriorated significantly. The reward for doing good work is always more work and rarely compensatory. Several members of the Executive Leadership Team will throw their own team members under the bus as soon as any fire comes in their direction. It's one thing to be cutthroat in a competitive business sense, but it is detestable to behave this way to one's own subordinates. Many roles in operations are full time putting out fires and performing manual workarounds for bugs that should have been addressed years ago. There is a huge gap between employees with 10+ years of experience and employees with <2 years of experience that continues to grow. This leaves a lot to be desired in terms of technical expertise. Per the SEC filing, the executive leadership team had a great year in terms of salary & bonus in 2020. The same cannot be said about me despite being promoted twice that year. Glassdoor ratings - given my comments above, compare the ratings from the “10+ years” or the “less than 1 year” to the ratings from the “2 to 8 years” range. It's clear this is where the problem lies. While the company is trying to be SaaS, the company culture is inherited from Mega Insurers and really has no link to what the environment seems to be in other SaaS companies (based on my Glassdoor research). Compare Clearwater to some top SaaS companies, and then compare it to mega insurance companies. You don't need to be a data scientist to see the relationship.
