What to expect in a Celonis Data Engineer interview: one candidate reports four rounds covering an online SQL test, a data modeling discussion, a business presentation and a department-head conversation.
$177K
Avg. Base Comp
$230K
Avg. Total Comp
4 rounds
Typical Rounds
Not reported
Process Length
This Data Engineer account describes four rounds, and it is more than a coding screen. The candidate began with an online SQL test on query writing and optimization, then met a hiring manager and a consultant. That second round was the most technical. The candidate was asked to walk through past projects, explain how slow SQL queries were diagnosed and fixed, and reason through a data modeling case by choosing entity attributes and defending the trade-offs.
Round three was a business presentation. The candidate says it tested whether technical work could be translated into business value, and it caught them a bit off guard, so it is worth rehearsing. The final round was with the head of the department and felt more like a culture and strategy conversation than another technical screen.
For preparation, have two or three concrete stories about query tuning, including how you read execution plans and where indexing helped. Practice explaining a modeling decision out loud, with the alternatives you rejected. Then build a short presentation on a past pipeline that leads with its business outcome. This candidate did not receive an offer and described slow pacing and unclear signals between rounds, so it is sensible to ask the recruiter about next steps after each stage. Because this guide rests on a single report, treat the round order as one example rather than a fixed format.
Synthesized from 7 candidate reports by our editorial team.
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Real interview reports from people who went through the Celonis process.
I went through four rounds of interviews at Celonis for a Data Engineer role. The first round was an online SQL test, which covered foundational query writing and optimization concepts. I found it straightforward but wanted to make sure I was thinking clearly about indexing and execution plans going in.
The second round was with the hiring manager and a consultant. This is where things got more substantive. They dug deep into my past data engineering experience, asking me to walk through specific projects and how I'd handled performance issues. They wanted concrete examples of how I'd diagnosed and fixed slow-running SQL queries. I also had to discuss data modeling scenarios in detail — they'd present a business case and ask me to think through which attributes I'd use for a particular entity, why I'd structure it that way, and what trade-offs I was making. It felt less like a quiz and more like a real design discussion.
Round three was a business presentation. This was the part that caught me a bit off guard — they wanted to see how I could translate technical work into business value, not just execute engineering tasks. Then came round four with the head of the department, which felt like a culture and strategy conversation more than another technical screening.
Overall, the process was well-structured and the interviewers were engaged. That said, the pacing felt a bit slow between rounds, and I never quite got clear signals on where things stood. The feedback loop could have been tighter.
Prep tip from this candidate
Prepare detailed stories about diagnosing and fixing slow SQL queries, and be ready to discuss data modeling trade-offs with reasoning — the hiring team spent considerable time on both. Also practice translating technical solutions into business impact, since the business presentation round was a key part of the evaluation.
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Sourced from candidate reports and verified by our team.
Topics based on recent interview experiences.
Featured question at Celonis
Write a SQL query to count transactions filtered by several criterias.
| Question | |
|---|---|
| Slow SQL Query | |
| Empty Neighborhoods | |
| 2nd Highest Salary | |
| Merge Sorted Lists | |
| Comments Histogram | |
| Closest SAT Scores | |
| Subscription Overlap | |
| Rolling Bank Transactions | |
| Top Three Salaries | |
| Experiment Validity | |
| String Shift | |
| Download Facts | |
| Random SQL Sample | |
| Minimum Change | |
| Last Transaction | |
| Customer Orders | |
| Prime to N | |
| Average Quantity | |
| Monthly Customer Report | |
| The Brackets Problem | |
| Upsell Transactions | |
| Top 3 Users | |
| Find the Missing Number | |
| Find the First Non-Repeating Character in a String | |
| Rectangle Overlap | |
| Manager Team Sizes | |
| Largest Salary by Department | |
| Month Over Month | |
| Third Purchase |
Synthesized from candidate reports. Individual experiences may vary.
The candidate reports an online SQL test covering foundational query writing and optimization concepts. It was described as straightforward, but indexing and execution plans were on the candidate's mind going in. Expect to write queries accurately and be ready to reason about performance.
The candidate reports a deeper technical conversation with a hiring manager and a consultant. It covered past data engineering projects, how slow SQL queries were diagnosed and fixed, and data modeling scenarios where they chose entity attributes and explained their trade-offs. It reportedly felt like a design discussion rather than a quiz.
The candidate reports a presentation round that tested how well technical work could be turned into business value. This caught them slightly off guard. Applicants may want to prepare a short walkthrough of a past project that leads with the business outcome rather than the implementation.
The final round was reportedly with the head of the department and felt more like a culture and strategy conversation than another technical screen. The candidate also noted slow pacing between rounds and unclear signals on where things stood, so asking about timelines and next steps may help.
