The interview process began with a 1-hour phone screen, which was pretty easy and nothing to be too nervous about. It did not feature standard LeetCode questions but instead focused on more real-world coding scenarios.
I was then invited for an on-site interview, which consisted of three rounds plus lunch. Don't expect obscure algorithms questions; the interviewers seemed more pragmatic, and every question was somewhat related to their business domain (e.g., log parsing, tagging).
Finally, I completed a take-home test. It was straightforward, but the devil was in the details. Be clear about what you would change or improve in the documentation you write. There were some implementation details that you had to decide without clarification from the prompt.
Overall, the process was easier than FAANG interviews but a little more time-consuming due to the take-home test. I would have preferred a longer on-site than a take-home test since I had to take the full day off from work anyway.
Because I had competing offers, they led with a strong offer upfront. They won't beat Google/Facebook, but if you have multiple offers or expect to, I recommend being candid about the companies you're interviewing with, and they'll do their best to be competitive.
I ended up taking the Datadog offer because they had the most interesting technical challenges.
Every question was related to Datadog's product.
Think about how you would implement the full stack.
The following metrics were computed from 38 interview experiences for the Datadog Software Engineer role in New York, New York.
Datadog's interview process for their Software Engineer roles in New York, New York is very selective, failing most engineers who go through it.
Candidates reported having very good feelings for Datadog's Software Engineer interview process in New York, New York.