There is a difference between what I call 'clever' and 'smart'. There are plenty of people that are fast on their feet at thinking about algorithmic-y type things. That doesn't translate into an ability to think through engineering problems, drive a project forward, cut through red tape, motivate peers, mentor the less experienced, identify market opportunities, behave ethically, build great teams .. I can go on. There is so much to this job other than manipulating binary trees, and swiftness at doing that at a white board is not a particularly good indicator of being able to think hard about novel problems. My best math professor, ever, had to ask the class to do the arithmetic and often we'd have to correct his algebra steps. He was fantastic, he just wasn't great at doing that stuff on his feet in front in front of an audience.

And, of course, not many jobs require novel algorithms; most require all other stuff. I'd give my eye teeth for an engineer that can just plod through and keep a project on schedule and budget. Don't see how the 'tough questions' identify her.

The downside to the methods Google etc use is they have a huge number of false negatives. They reject tons of great engineers. This works out well when you constantly have thousands of great engineers applying to work for your company.

It does not work well at all if you are a normal company.

When you're a household name and most engineers view your company as a top place to go and you're getting thousands of resumes a day, you have the ability to filter differently than most folks.