Junior Data Engineer Interview Questions UK: 8 Real Questions and What Interviewers Want

Applying for a Junior Data Engineer job in the UK? Here is what you are likely to be asked. These questions come from our Junior Data Engineer question bank of 16 questions, written for UK employers at junior level.

Eight Junior Data Engineer interview questions, and what the interviewer is thinking

1. What does a typical day as a junior data engineer involve, and what draws you to the role?

Why they ask: They want to see you understand the work is mostly building and maintaining pipelines, not glamorous modelling.

2. How would you find and remove duplicate records in a table using SQL, and how would you do it safely?

Why they ask: Duplicate handling is a daily task and shows whether you respect production data.

3. Which Python libraries have you used for data work, and how would you process a CSV file too large to fit in memory?

Why they ask: Python is the core language for most junior data engineering tasks and they want practical awareness of memory limits.

4. What is the difference between OLTP and OLAP systems, and why does it matter when designing pipelines?

Why they ask: It tests whether you understand why data has to be moved and reshaped before analysis.

5. What is normalisation, and when might you deliberately denormalise data?

Why they ask: Data modelling fundamentals underpin every table a data engineer builds.

6. How do you use Git in a team project, and what makes a good pull request?

Why they ask: Version control and code review are standard working practice in engineering teams.

7. You have built your first pipeline and an analyst tells you the row count in the warehouse does not match the source. What do you do?

Why they ask: They are testing methodical debugging and how you handle your own possible mistake.

8. Tell me about a time you tracked down a difficult bug in code or data.

Why they ask: Debugging is a large part of the job and the answer shows your method under pressure.

A sample answer to question 1

What does a typical day as a junior data engineer involve, and what draws you to the role?

As I understand it, a junior data engineer spends most of the day extending and maintaining pipelines that move data from source systems into a warehouse or lakehouse. That means writing SQL and Python, picking up tickets in a sprint, reviewing pull requests, checking overnight job runs in a tool like Azure Data Factory or Airflow, and fixing anything that failed. There is also plenty of talking to analysts and data scientists about what they need and why a number looks wrong. What draws me in is that I enjoy making things reliable. At university I built a pipeline pulling public transport data into PostgreSQL, and the satisfying part was adding tests and alerts so it ran without me watching it. I like that good data engineering is invisible when it works, and that everyone downstream depends on it. I also want to learn cloud tooling and software engineering practice properly alongside experienced colleagues.

Common mistake to avoid: Describing it as mostly machine learning; Giving only enthusiasm with no detail of the work

Want the rest?

Full model answers, key points and common mistakes for all 16 questions are on the Junior Data Engineer interview questions page. The first five are free, no sign-up needed.