The call with the recruiter was straightforward and to the point. The second interview was a one-hour session split equally between product knowledge and SQL. The product knowledge portion was simple—if you’ve watched YouTube videos on FAANG Data Scientist interviews, you’ll have a good foundation to do well. The interviewer was a sweet person and they even mentioned I did very good. However, the SQL portion is what caused me an issue (I think). As a Data Scientist with six years of experience, including time at Meta, I found their approach outdated. It felt like something from the 2010s when companies were unsure whether they needed a Data Scientist or a Data Engineer. The interviewer didn’t turn on their camera, which made the interaction feel disengaged, and they seemed distracted throughout. The SQL prompt wasn’t overly difficult but was highly impractical—something you’d never encounter in a real-world scenario. To make matters worse, the coding environment didn’t execute your code, forcing you to mentally process everything under strict time constraints. It felt more like a test of memorization than actual problem-solving skills. My main takeaway was, “DoorDash tries to present itself as a FAANG-like company, but their analytics department is stuck in the past.” If you’re preparing for a SQL interview with DoorDash, I honestly don’t know what would adequately prepare you for their outdated and poorly administered process. I thought we had moved past asking irrelevant SQL trivia in technical interviews. For interviewers, make sure you answer the question fast and hopefully the employee administering your interview will be more engaged than mine! Good luck!