
Thoughtworks Data Engineer Interview Questions
& Process
Real candidates share what happened, how many rounds they had,
and how the experience turned out.
Based on 17 interview experiences · FREE TO READ
Candidate interview experiences
First-hand accounts from people who interviewed at Thoughtworks.
Data Engineer
I went through Thoughtworks’ hiring process, and honestly, it was a frustrating experience. My resume got shortlisted, I cleared two technical rounds where I answered every question, and then—surprise—I was rejected in the managerial round. The reason? Apparently, I haven’t “explored” technologies like streaming, AI, and trending data systems. Funny, because none of these were even mentioned in the JD as mandatory skills. If these were essential, they should have been listed clearly so that I wouldn’t have applied in the first place. What’s even more baffling? I still managed to clear the technical rounds, so clearly, my skills were good enough up until then. Also, I was asked an optimization question, to which I provided multiple valid Spark optimization techniques. There were no follow-up questions, so I assumed my answer was satisfactory. But apparently, assumptions don’t work when dealing with a process as inconsistent as this one. If a company wants candidates with specific experience, they should be transparent from the beginning instead of leading people on for four weeks only to reject them for reasons that were never part of the requirements. This kind of hiring process doesn’t just waste candidates’ time—it also reflects poorly on the company’s professionalism.
- Tell me about your SQL knowledge, both theoretical and practical.
- Tell me about your Python knowledge, both theoretical and practical.
- Tell me about your PySpark knowledge, both theoretical and practical.
Lead Data Engineer
First up was a 15 min chat with the recruiter. Then there were 3 actual rounds: the first was a hands-on technical challenge focusing on PySpark. Round two was another technical session, this time digging into Apache Flink and streaming pipelines. The final round was with the head of engineering, and it was more about leadership and culture.
- What are the differences between Apache Flink and Spark?
Data Engineer
The process was a bit long, with 4 stages. First contact with HR, then a technical interview, a cultural one, and finally an interview with leadership. The whole process took about 3 months, but I was called back after 6 months because they were closing deals with new clients. Since I wasn't in a hurry, the wait was fine. The recruiter was very helpful and answered all my questions.
- What is your experience as a data engineer?
- Can you tell me about your projects?
- Can you communicate in English regarding your experience?
Thoughtworks Data Engineer Interview Questions
Quoted word for word from Thoughtworks interview reports.
“What are the differences between Apache Flink and Spark?”
Read reports →“Have you heard of data mesh?”
Read reports →“Tell me about Spark's internal optimizations for SparkSQL and other related components.”
Read reports →“Could you describe your approach to calculating a moving average on data using Spark RDDs?”
Read reports →“Are you familiar with the fundamental concepts of the Hadoop Ecosystem?”
Read report →“What are your perspectives on societal inequalities?”
Read report →“Could you specify details about data pipelines and related items?”
Read report →“Did you do unit testing on the tasks?”
Read report →“Tell me about your PySpark knowledge, both theoretical and practical.”
Read report →Formats, difficulty and experience
Across all 17 Thoughtworks interview reports.