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Apple Data Engineer Interview Experience — Rejected After Two Technical Rounds, But the Nicest Interview Yet

RejectedTech screenInterviewed 2025-11

Apple Maps – Metrics Engineering team I'd never heard of this role before either. I looked into it a lot, and it feels kind of like a Data Engineer (Analytics-leaning) role — designing data pipelines for various Apple Maps features and building metrics to measure the app's performance. A recruiter reached out to me, and I went into the interview just to give it a try. I ended up failing, but this…

Apple Maps – Metrics Engineering team

I'd never heard of this role before either. I looked into it a lot, and it feels kind of like a Data Engineer (Analytics-leaning) role — designing data pipelines for various Apple Maps features and building metrics to measure the app's performance.

A recruiter reached out to me, and I went into the interview just to give it a try. I ended up failing, but this was honestly the best interview experience I've had so far! Both the hiring manager and the technical interviewer were incredibly nice and gave me a ton of positive feedback.

I also looked into a lot of background info — Apple Maps isn't a revenue generator, but it's part of the Apple ecosystem and gets integrated into features like Weather, Photos, Siri, and Location Services. The team has a lot of long-tenured employees, very low turnover, and the culture is really solid.

There were two technical rounds total: the first was 45 minutes of Python, the second was 45 minutes of SQL and database design.

The first round's Python question was OOP-focused. I didn't copy down the exact question, but roughly, it went like this:

You're given a Parent class, then a Child class:

class Parent:
    def __init__(self, l):
        self.l = l
        self.lf = set(str(s) for s in self.l)
        self.ldf = {}
        for item in self.l:
            s = str(item)
            if s not in self.ldf:
                self.ldf[s] = 1
            else:
                self.ldf[s] += 1

class Child(Parent):
    def most_frequent_key(self):
        # find the highest count manually (you can't use max())
        # you need to write this part yourself
        return output_list

# Example
queries = ['park', 'Park', 'McDonalds', 'apple', 'Apple Park', 'park', 'Park']

# first you write x = Child(queries)
# then print("most frequent:", x.most_frequent_key())

The second round was 45 minutes of SQL and database design; the source doesn't provide its individual questions.

Good luck to everyone, hope you all interview well and land lots of offers!

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