McKinsey Data Engineer Interview GuideMcKinsey Data Engineer Interview Guide

Overview

Getting ready for an Data Engineer interview at McKinsey? The McKinsey Data Engineer interview span across 10 to 12 different question topics. In preparing for the interview:

  • Know what skills are necessary for McKinsey Data Engineer roles.
  • Gain insights into the Data Engineer interview process at McKinsey.
  • Practice real McKinsey Data Engineer interview questions.

Interview Query regularly analyzes interview experience data, and we've used that data to produce this guide, with sample interview questions and an overview of the McKinsey Data Engineer interview.

McKinsey Data Engineer Salary

$117,662

Average Base Salary

$119,899

Average Total Compensation

Min: $93K
Max: $175K
Base Salary
Median: $110K
Mean (Average): $118K
Data points: 21
Min: $102K
Max: $138K
Total Compensation
Median: $120K
Mean (Average): $120K
Data points: 3

View the full Data Engineer at Mckinsey & Company salary guide

McKinsey Data Engineer Interview Process

Typically, interviews at McKinsey vary by role and team, but commonly Data Engineer interviews follow a fairly standardized process across these question topics.

We've gathered this data from parsing thousands of interview experiences sourced from members.

McKinsey Data Engineer Interview Questions

Practice for the McKinsey Data Engineer interview with these recently asked interview questions.

Question
Topics
Difficulty
Ask Chance
Probability
Hard
Very High
Database Design
Easy
Very High
Python
R
Medium
Very High

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View all Mckinsey & Company Data Engineer questions

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