Oracle Data Engineer interview typically runs 2 rounds: recruiter screening, technical HackerRank interview. It usually takes about 1-2 weeks and is straightforward, with a short behavioral intro before coding.
$175K
Avg. Base Comp
$243K
Avg. Total Comp
3
Typical Rounds
2-3 weeks
Process Length
Our candidates report that Oracle’s interview style can feel deceptively simple: the bar is less about exotic system design and more about whether you can execute cleanly under a very direct prompt. In the experience we saw, the technical portion was a classic fundamentals check, and the coding task itself was straightforward enough that the real separator was precision with edge cases — in this case, getting Roman numeral subtraction rules right without overcomplicating the solution. That tells us Oracle is looking for engineers who can translate requirements into correct, readable implementation quickly, not candidates who rely on flashy algorithms to stand out.
A recurring theme is that Oracle also wants a credible story for why you fit the role before the coding even starts. The screening conversation was described as high-level fit plus basic behavioral questions, which suggests the company is using early conversation to verify communication, role alignment, and whether you can speak clearly about your background. We also noticed the behavioral prompt around client pushback, which is a subtle signal that they care about how you handle disagreement and constraints in a business-facing environment. For data engineering candidates, that combination usually means the strongest interviews are the ones that feel grounded, practical, and calm — especially when the technical question is intentionally unglamorous.
Synthesized from 1 candidate report by our editorial team.
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Featured question at Oracle
Write a query to get the number of customers that were upsold
| Question | |
|---|---|
| Integer to Roman | |
| Normalize Grades | |
| Random Forest Explanation | |
| Resumable Fact Table Load | |
| Basic Regex | |
| Count Transactions | |
| Binary Tree Conversion | |
| Slow SQL Query | |
| Binary Tree Validation | |
| Assumptions of Linear Regression | |
| Concurrent LLM Serving | |
| Scalable Data Pipelines | |
| Azure Kubernetes Infrastructure | |
| Client Solution Pushback | |
| Pathfinder in Maze | |
| Safe Deployments | |
| Relational Migration | |
| Why Do You Want to Work With Us | |
| Your Strengths and Weaknesses | |
| LRU Cache 1 | |
| Empty Neighborhoods | |
| 2nd Highest Salary | |
| Comments Histogram | |
| Merge Sorted Lists | |
| Rolling Bank Transactions | |
| Top Three Salaries | |
| Closest SAT Scores | |
| Subscription Overlap | |
| Experiment Validity |
Synthesized from candidate reports. Individual experiences may vary.
A recruiter reached out on LinkedIn with a link to apply, and the candidate then submitted an application. This appears to be the first contact before any formal screening.
The first live conversation focused on the candidate’s background, high-level fit for the role, and a few basic behavioral questions. It served as an early filter before the technical assessment.
This round started with about 10 minutes of behavioral questions, then moved into a LeetCode-style coding problem on HackerRank. The problem was straightforward and tested fundamentals and clean implementation, such as converting an integer to a Roman numeral using the candidate’s preferred language.
