Delivery Hero Data Analyst candidates report HR screening, SQL assessment, pricing and experimentation cases, and a hiring-manager discussion of past analytics work.
$88K
Avg. Base Comp
$100K
Avg. Total Comp
3-4 rounds
Typical Rounds
2-4 weeks
Process Length
Delivery Hero Data Analyst interviews reported here combine practical SQL work with a business discussion about pricing and experiment design. One candidate described four rounds—HR, a SQL/case round, a pricing analytics case, and a hiring-manager conversation—while another described three total rounds including HR, an online SQL test, and a hiring-manager interview with a case study. Prepare to explain analytical trade-offs, not just calculate a metric.
For SQL, candidates report joins, CTEs, window functions, and aggregations, including comparing average order value and conversion before and after a delivery-fee change and finding users with a significant drop in order frequency. The pricing case focused on whether increasing delivery fees could improve profitability while affecting conversion, order frequency, revenue, contribution margin, retention, and customer segments.
Experimentation was a central thread in the detailed report: candidates may need to explain an A/B test, select a primary metric, assess statistical significance, and account for seasonality or different city-level customer mixes. Be ready to distinguish correlation from causation when a price change coincides with revenue growth. The hiring-manager conversation may also ask for a clear walkthrough of a prior data project and follow-up on technical skills or international collaboration. The reported evidence is limited to two candidate accounts, so stage order and total rounds can vary.
Synthesized from 2 candidate reports by our editorial team.
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Real interview reports from people who went through the Delivery Hero process.
The whole interview process was very smooth and felt pretty structured from start to finish. I had three rounds in total. The first was an HR screening, and it was mostly about my background and whether I had experience working with international teams. That part was pretty conversational and set a positive tone. After that came an online test, which was a standard SQL assessment. The difficulty was average, nothing too tricky, but it did require being comfortable with SQL basics and moving through the questions efficiently. The last round was with the hiring manager, and that one went deeper into my past work experience. I was asked to walk through a data project I had worked on, and then they followed up to understand my technical skills more closely. There was also a case study question in the process, so it was not just about answering SQL problems but also showing how I think through business situations. Overall, the recruiters and interviewers were supportive and created a good vibe throughout the process, which made it less stressful than I expected. I did not get an offer in the end, but the process itself was smooth and fair. My main takeaway is to be ready to discuss your own projects clearly, especially if they involve cross-functional or international collaboration, and to practice standard SQL plus a simple case study discussion.
Prep tip from this candidate
Be ready for a standard SQL assessment and a case study question, but don’t overlook the HR screen’s focus on international team experience. Also prepare a clear walkthrough of one past data project, since the hiring manager dug into that quite a bit.
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Sourced from candidate reports and verified by our team.
Topics based on recent interview experiences.
Featured question at Delivery Hero
How would you assess the validity of the result?
| Question | |
|---|---|
| Bagging vs Boosting | |
| Uber User Journey | |
| Clickstream Data | |
| Hurdles In Data Projects | |
| Target Indices | |
| Testing Price Increase | |
| Concurrent LLM Serving | |
| Slow SQL Query | |
| DDoS Attack Response | |
| Finding the Maximum Number in a List | |
| Diagnosing Query Speed Degradation | |
| Testing Constraints | |
| Stories Feature Change | |
| Client Solution Pushback | |
| Relational Migration | |
| Why Do You Want to Work With Us | |
| Free Shipping Mention Test | |
| Evaluating Revenue Decline | |
| Generative AI Privacy | |
| Delivery Fees | |
| Correlation in Regression | |
| Linear vs Logistic Regression | |
| Empty Neighborhoods | |
| 2nd Highest Salary | |
| Rolling Bank Transactions | |
| Customer Orders | |
| Monthly Customer Report | |
| Comments Histogram | |
| Closest SAT Scores |
Synthesized from candidate reports. Individual experiences may vary.
Candidates report an opening HR conversation about background; one candidate was asked about experience working with international teams. Prepare a concise account of relevant collaboration and analytics experience.
Candidates report either an online SQL test or a SQL/case round. Topics included joins, CTEs, window functions, and aggregations, with practical order, conversion, and frequency analysis.
One candidate reported a delivery-fee case requiring a recommendation on price changes, customer segmentation, and measurement of conversion, order frequency, revenue, and contribution margin.
Candidates report a hiring-manager conversation that may go deeper on a previous data project, technical skills, and case-study reasoning. Explain assumptions, risks, and how you would validate a recommendation.
