Siemens Data Analyst candidates describe a technical interview covering BI tools, ETL, data quality or logic puzzles, then a CV-focused HR or personal fit conversation. HR follow-up was slow in two reports.
$116K
Avg. Base Comp
$143K
Avg. Total Comp
Not reported
Typical Rounds
Not reported
Process Length
Three candidates who interviewed for the Siemens Data Analyst role describe quite different technical rounds, so prepare for the data work and for the conversation about your background.
The candidate who received an offer describes two phases: a technical interview and a personal fit interview. The technical session focused on BI tools, databases and data quality. It included scenarios about complex data workflows, ETL frameworks such as Informatica and AWS Glue, cleaning a large messy dataset, and accounting and business questions that tied analysis back to outcomes. The personal fit interview covered the CV, why Siemens, and what drew the candidate to the role.
Another candidate who did not advance had a very different technical round: a CV walkthrough, then about 45 minutes of logic puzzles, problem-solving exercises and some object-oriented questions, followed by an HR round that went back over the CV. That candidate had expected SQL or statistics and did not get them, so a little puzzle practice is reasonable alongside your data skills.
The November 2025 candidate was asked how they would ensure the accuracy of data. They answered with source checks, reconciliation against known totals and flagging anomalies. The feedback was that they were technically strong but should have had more work experience, so bring concrete examples of the impact your projects had.
Two of the three describe slow HR communication, and one heard the outcome about two weeks after the final conversation, after several follow-ups. Keep track of dates and send a polite nudge if an update slips.
Synthesized from 5 candidate reports by our editorial team.
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Real interview reports from people who went through the Siemens process.
The whole thing took two months with interviews spread out—basically one per month—and the HR communication was completely broken. No feedback after each round, no updates on next steps, nothing. Just silence. I had to email them multiple times weeks later just to get any response at all. Honestly pretty frustrating. The interviewers themselves though, they were really nice and pleasant, so at least that part of the experience wasn't a headache.
I went through behavioral questions asking stuff like "Tell me about the last time you learned something new" and "Who's your inspiration?" Pretty standard stuff to get you talking about your background. Then there was a technical round with whiteboard data structure questions—nothing crazy difficult but it tests whether you can think clearly when you're coding on the spot. And finally an in-person interview where they focused on my project experience and what I'd actually delivered.
I didn't get the offer at the end. The interviews themselves weren't bad or unfairly difficult, but the whole process felt unnecessarily prolonged and the HR side was just completely dysfunctional. Some actual communication along the way would've made it a lot better.
Prep tip from this candidate
Go in with concrete examples of professional learning—they ask about the last time you learned something new. Be ready to discuss your inspirations. For the technical round, practice data structures problems on a whiteboard.
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Sourced from candidate reports and verified by our team.
Topics based on recent interview experiences.
Featured question at Siemens
Given an integer N, write a function that returns all of the prime numbers up to N
| Question | |
|---|---|
| Size of Joins | |
| Find Duplicate Numbers in a List | |
| Hurdles In Data Projects | |
| Multi-Reaction | |
| RAG Strict Source Control | |
| Overfit Avoidance | |
| Safe Deployments | |
| The Pirate’s Hunt | |
| Client Solution Pushback | |
| Tableau Filters and Parameters | |
| Your Strengths and Weaknesses | |
| Data Cleaning Experiences | |
| 2nd Highest Salary | |
| Bagging vs Boosting | |
| Bank Fraud Model | |
| Booking Regression | |
| Instagram TV Success | |
| Covariance vs Correlation | |
| Random Forest Explanation | |
| Lasso vs Ridge | |
| Assumptions of Linear Regression | |
| Out of Stock Inventory | |
| Bias vs. Variance Tradeoff | |
| Classification and Regression | |
| Seller Type Modeling | |
| Data Preparation for Imbalanced Data | |
| Loan Model | |
| D2C Socks e-Commerce | |
| String Palindromes |
Synthesized from candidate reports. Individual experiences may vary.
The offer candidate was asked about BI tools and databases, complex data workflows, data quality issues, ETL frameworks like Informatica and AWS Glue, and cleaning a large messy dataset. Another candidate had a CV walkthrough and about 45 minutes of logic puzzles and object-oriented questions. Expect the content to vary.
The offer candidate and the candidate who faced logic puzzles both describe a second conversation centered on the CV. Questions included why Siemens and what drew the candidate to the role. The puzzle-round candidate was pressed on background and experience, so have a concise story that links your past work to the job.
One candidate received an offer, and others did not advance. The November 2025 candidate was told they were technically strong but needed more work experience, and heard the result about two weeks after the final conversation, after several HR follow-ups. Another also found HR slow to respond. Note dates and follow up politely.
