Nielsen Data Engineer Interview: Real Spark + Python + SQL Questions (My Experience)
Data Engineer Real Interview Experience
In this video, I’m sharing my real interview experience with Nielsen for a Data Engineer role. I’ll walk you through the hands-on coding questions, practical Spark scenarios, SQL problems, and real-time data engineering challenges that were asked.
If you're preparing for a Data Engineer interview, especially in companies like Nielsen that work heavily with media analytics and large-scale data processing, this video will help you understand:
✅ Spark & PySpark coding questions
✅ SQL window functions & optimization scenarios
✅ Data pipeline design questions
✅ AWS & Big Data ecosystem discussions
✅ Real-time problem-solving approach
✅ Scenario-based and practical interview rounds
This is not theory — this is based on actual interview experience.
If you're targeting roles in:
1. Media Analytics companies
2. Big Data Engineering roles
3. Product-based companies
4. MNC Data Engineer positions
This video will give you clarity on what to expect and how to prepare.
💬 If this helps you, comment your doubts below.
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00:00 Video Intro
00:31 Introduction Question
00:42 Python – Count Occurrence of X
01:12 Spark – Second Highest Salary Department Wise
01:58 What is the difference between RANK, DENSE_RANK, and ROW_NUMBER?
02:32 Python - Find Number That When Added With X Gives Y
02:56 Broadcast Join in PySpark
03:28 Cluster Configuration Calculation
04:38 SQL - Manager With Most Direct Reports
05:04 Interview Tips