
Neudesic Data Engineer Interview Questions
& Process
Real candidates share what happened, how many rounds they had,
and how the experience turned out.
Based on 6 interview experiences · FREE TO READ
Candidate interview experiences
First-hand accounts from people who interviewed at Neudesic.
Azure Data Engineer
I applied on the website and a recruiter contacted me. Then there were 3 interview rounds: the first was coding, the second technical, and the third technical. I passed all of them, but the recruiter stopped responding. Later I found out it was due to salary expectations not being met.
- Pure coding questions focusing on SQL and Spark, with Spark questions on their platform and SQL on notepad.
- Technical questions of easy to medium difficulty, covering both theory and coding.
- Technical questions of easy to medium difficulty but with more depth.
Azure Data Engineer
The interview process included 1 hands-on round where I had to build an ADF pipeline, and 2 technical rounds. The first technical round covered basic questions about ADF concepts like linked service, function vs SP, dataset, and activities. The second round was based on my self-introduction.
- Azure Data Factory basics
- basics on Azure ETL
- SQL basics
Data Engineer
I went through 2 rounds of interviews. The first was a technical round where I had to solve some SQL problems, which I think went okay. The second technical round felt off, with questions that didn't seem relevant to the Data Engineer role. The interviewer was quite negative, acting like they knew everything and constantly trying to prove me wrong. It was discouraging, and despite answering some scenario questions on ADF well, the interviewer's attitude made my efforts feel pointless.
- Solve this SQL question and provide the output.
- Can you answer some questions about PySpark?
- What are your thoughts on scenario-based questions regarding ADF?
Neudesic Data Engineer Interview Questions
Quoted word for word from Neudesic interview reports.
“Create a SQL query to identify and return the top 5 customers based on their total order amounts.”
Read reports →“Write a PySpark job to eliminate duplicate events. A duplicate is defined as having the same user_id, event_type, and event_timestamp. For each user, ensure you retain only the most recent event.”
Read reports →“Given a customer dataset with missing age and city information, write code to substitute NULLs. Use the average age for missing ages and 'Unknown' for missing cities.”
Read reports →“Solve this SQL question and provide the output.”
Read reports →“Can you answer some questions about PySpark?”
Read report →“Can you write some SQL queries?”
Read report →“Do you have experience with PySpark questions?”
Read report →“What are your thoughts on scenario-based questions regarding ADF?”
Read report →“Tell me about your projects.”
Read report →Formats, difficulty and experience
Across all 6 Neudesic interview reports.