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Apple data interview guide

Device, App Store and services analytics with a strong focus on data quality.

typical interview loop

  1. 1.Recruiter screen
  2. 2.Technical screen: SQL plus a Python data-manipulation exercise
  3. 3.Onsite: data modeling / pipeline design, coding, behavioral
  • › Handle NULLs and duplicates explicitly.
  • › Be ready to explain assumptions about messy source data.

most-tested topics

JOIN
3
groupby
3
GROUP BY
3
dates
3
Window functions
2
filtering
1

Based on 18 reconstructed Apple-style questions.

practice path

0 free · 18 Pro
  1. 1Active subscription value by plansqlMedium
  2. 2Apps that never soldsqlMedium
  3. 3Average session length per appsqlMedium
  4. 4Crash rate per apppandasMedium
  5. 5Daily engagement pivotpandasHard
  6. 6Device activations by countrysqlEasy
  7. 7Longest daily usage streakpythonHard
  8. 8Minutes per apppandasEasy
  9. 9Month-over-month revenue changesqlHard
  10. 10Monthly App Store revenuesqlMedium
  11. 11Refund window checkerpythonMedium
  12. 12Revenue by app categorysqlEasy
  13. 13Running revenue by monthsqlHard
  14. 14Short-lived subscriptionssqlHard
  15. 15Spend per user with device modelsqlMedium
  16. 16Subscription renewal schedulepythonMedium
  17. 17Top spender per countrypandasMedium
  18. 18Validate device serialspythonEasy

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