Senior Data Engineer
Posted Sep 23, 2026 · We last checked this listing on Oct 6, 2026
Likely interview questions for this role
Written from this job description, not a generic list. Each one notes what the interviewer is really checking.
About your past
Tell me about a modernization project where you moved older data processes to a cloud platform. What went wrong?
What they are checking: Whether they have real migration experience and can talk honestly about the hard parts.
Tell me about how you have guided less experienced data engineers.
What they are checking: Whether they share knowledge and raise the team's standards, which the posting asks for.
How do you work with analysts and business teams to define what a new data warehouse application should do?
What they are checking: Whether they collaborate early so solutions meet real reporting needs.
What would you do
A Databricks job that used to run in 20 minutes now takes two hours. How do you find the cause?
What they are checking: Whether they troubleshoot performance methodically, looking at data growth, partitions and cluster settings.
A business team says the numbers in a dashboard are wrong. How do you investigate?
What they are checking: Whether they trace data lineage calmly and communicate clearly with the business while fixing it.
About the work
Walk me through how you would design a pipeline in Azure and Databricks that loads sales data into a data warehouse every night.
What they are checking: Whether they can lay out ingestion, transformation, storage and scheduling in a way that scales and recovers from failure.
How do you decide between a star schema and a more normalized design for a BI data warehouse?
What they are checking: Whether they design for how analysts will actually query and report on the data.
How do you test ETL code so you trust the numbers before they reach a report?
What they are checking: Whether they build data quality checks into pipelines instead of finding errors after business users do.
What do you look for when you review another data engineer's code?
What they are checking: Whether they check for correctness, maintainability and standards, since the role keeps quality high through code reviews.
Where do you see AI automation helping data engineering work, and where would you be careful?
What they are checking: Whether they have a practical, grounded view of using AI to improve data accuracy and efficiency.
How do you handle slowly changing dimensions, like a customer moving to a new sales territory?
What they are checking: Whether they understand how to keep historical reporting accurate when business data changes.
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Practice this out loudThe full job description
As published by Uline.