SAP Data Engineer interview typically runs 3 rounds: assessment, phone interview, HR interview. It usually takes a few weeks and is fairly lean, with limited extra interaction.
$118K
Avg. Base Comp
$271K
Avg. Total Comp
3
Typical Rounds
3-5 weeks
Process Length
Our candidates report that SAP’s data engineering interviews are less about proving you can name tools and more about showing you can operate inside an enterprise software environment. A recurring theme is the need to connect past work to business context — one candidate said they had to explain previous roles and how they handled work, not just describe technical projects. That lines up with the broader feel of the process: even when the questions were centered on data engineering, the interviewers kept pulling the conversation back to how the work supports SAP’s customers and products.
We’ve also seen that SAP does not stay at the surface level of experience. Multiple candidates noted that the team mixed practical data engineering discussion with fundamentals, including a basic linear regression question, which suggests they’re checking whether you understand the core concepts behind the work, not just the implementation details. The strongest signal here is clear, crisp storytelling about your background paired with enough technical grounding to handle a quick pivot into fundamentals. Candidates also mentioned being asked about SAP-specific knowledge, so the non-obvious make-or-break factor is whether you can speak fluently about enterprise systems and still sound precise when the conversation turns technical.
Synthetized from 1 candidates reports by our editorial team.
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Topics based on recent interview experiences.
Featured question at Sap
Given an integer N, write a function that returns all of the prime numbers up to N
| Question | |
|---|---|
| Cyclic Detection | |
| Hurdles In Data Projects | |
| Equivalent Index | |
| Target Indices | |
| Word Frequency | |
| Flatten N-Dimensional Array to 1D Array | |
| Z and t-Tests | |
| Binary Tree Validation | |
| Dijkstra implementation | |
| String Palindromes | |
| Foreign Key Constraints | |
| Why Do You Want to Work With Us | |
| Your Strengths and Weaknesses | |
| Linear Regression Parameters | |
| Time Series Discrepancies | |
| Empty Neighborhoods | |
| 2nd Highest Salary | |
| Top Three Salaries | |
| Comments Histogram | |
| Merge Sorted Lists | |
| Closest SAT Scores | |
| Experiment Validity | |
| Subscription Overlap | |
| Rolling Bank Transactions | |
| Download Facts | |
| Random SQL Sample | |
| Top 3 Users | |
| Last Transaction | |
| Manager Team Sizes |
Synthesized from candidate reports. Individual experiences may vary.
The process starts with an assessment focused on data engineer fundamentals and practical problem-solving. Candidates should expect questions that test core technical knowledge, including basics like linear regression, along with broader understanding of the SAP ecosystem and the business context of the role.
After the assessment, candidates go through phone interviews where they explain previous roles, past work experience, and how they handled responsibilities in prior positions. These conversations are not purely technical; interviewers also look for clear communication, business awareness, and the ability to connect your background to SAP’s needs.
The final stage is an in-person interview that continues to cover technical data engineering topics while also probing SAP-specific knowledge and overall fit. Candidates are expected to speak confidently about their experience, demonstrate solid fundamentals, and show they understand the broader business side of the role before a final decision is made.