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Nielsen Data Engineer Interview Questions
& Process

Real candidates share what happened, how many rounds they had,
and how the experience turned out.

Based on 15 interview experiences · FREE TO READ

2.8 Rounds average
Average Typical difficulty
53.3% Positive experience

Candidate interview experiences

First-hand accounts from people who interviewed at Nielsen.

Showing 3 of 15
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Big Data Engineer

Engineering · more than a year ago

Mid Average Negative experience No offer 3 rounds
Interview process
Recruiter call Technical screen Technical screen
Interview formats
Technical Coding

The interview had 3 stages. The first stage was a screening round to test domain knowledge about the job role. It had questions from SQL, SCALA/Python, and Spark. SQL had simple GroupBy questions. Spark had basic aggregation functions. Python was about finding even numbers. There were also questions from spark/command line/aws/Apache DAG. The second round was unexpected, with questions about spark-submit syntax and UDFs. The interviewer had audio issues, making it hard to understand. Questions included connecting Spark with Oracle/Hive, SQL join types, connecting Spark with different databases and AWS S3, removing duplicates from tables, UDF syntax, spark-submit syntax, and creating Hive tables.

Confirmed questions7 questions
  • What are the different types of joins in SQL?
  • How would you connect Spark with different databases, and can you provide the syntax for it?
  • How would you connect AWS S3 with Spark?
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Nielsen

Data Engineer

Engineering

Senior Average Neutral experience No offer 4 rounds
Interview process
Recruiter call Onsite Background check Phone screen
Interview formats
Technical Behavioral

Started with a phone interview to get a general sense of my background. Then I had an onsite interview that covered both technical and behavioral aspects. The next day there was a short HR interview, and I got positive feedback suggesting an offer was likely. However, the following day, the situation changed. It seemed the original position was on hold, and they believed I'd be a better fit for a different role. This led to a technical phone call with another team, but their requirements, focused on core AWS skills, were different from the initial job description and the interview didn't last long. Ultimately, no offer was extended. It felt like one team was interested but couldn't meet my salary expectations, even though they initially agreed. The other team's focus on specific AWS skills didn't align with my experience for that particular interview.

Confirmed questions2 questions
  • Can you discuss your experience with Spark?
  • Were there any algorithm or coding challenges during the interview process?
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Nielsen

Data Engineer

Engineering

Entry Average Positive experience Accept offer 2 rounds
Interview process
Recruiter call Technical screen
Interview formats
Coding Technical Behavioral

Had a general intro, then we talked about my prior tech stack. They asked about the scale of data I've handled, what I did, and what effect it had. Then some coding challenges: finding the longest substring with unique chars, and checking if two strings are anagrams in linear time without sorting. Finally, a SQL problem about identifying products with prices that constantly went up month over month from a pricing table.

Confirmed questions2 questions
  • Basic questions on Spark, Python, and SQL were asked.
  • There were also some questions about Data Modelling.

Nielsen Data Engineer Interview Questions

Quoted word for word from Nielsen interview reports.

Write a function to replace the second occurrence of a character in a string with '#'.

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How would you split words in a file and count their frequency using PySpark?

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What distinguishes a POST API request from a PUT API request?

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How would you count the occurrences of an element within a list?

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Formats, difficulty and experience

Across all 15 Nielsen interview reports.

Interview formats

Technical 39.5%
Coding 36.8%
Behavioral 15.8%
System Design 5.3%
Other 2.6%

Interview difficulty

Easy 13.3%
Average 60%
Difficult 26.7%

Candidate experience

Negative 40%
Positive 53.3%
Neutral 6.7%