Expedia (IT) interview process & guide 2026
Everything we know about interviewing at Expedia (IT): the process stage by stage, what each round tests, compensation by level, and reports from candidates who interviewed.
- 1Recruiter or initial screening call
- 2Online assessment or online coding assessment
- 3Technical interviews, potentially multi-round, including panels
- 4Leadership or HR screening panel (if applicable)
Interviewing at Expedia (IT)
You will usually get an interview loop that mixes algorithm and coding practice with communication. In the reported technical interviews, you may do one or more technical interviews that include coding assessments and system design discussions, and there are also reports of behavioral conversations split alongside technical work.
What the process tests is strongly aligned to Data Structures, Algorithms, Machine Learning fundamentals, Data Engineering, and related topics like Feature Engineering and Data Pipelines. Across candidate reports and the extracted topic prominence data, expect frequent evaluation of problem solving, coding ability (including Python in the topic mix), model evaluation for ML roles, and clear communication of your reasoning.
In reported processes, a recruiter or recruiter-style screening call is an early step, then you may move into online assessments and multi-round technical interviews, sometimes with panel components. The candidate reports show frequent OA or timed coding, and the overall offer rate across all reported candidates is 3.7%, with difficulty skewed toward medium (75.9%).
The most useful non-obvious signal from the data is that the loop is not just about getting to a correct answer. The topic data and the reported formats repeatedly include communication skills and documenting analytical steps, alongside DSA and ML/engineering fundamentals, so you should explicitly explain your reasoning as you solve and as you review or discuss systems.
How hard is the Expedia (IT) interview?
Aggregated from 107 interview experiencesAbout 1 in 3 candidates with a known outcome convert.
The interview process, end to end
4 rounds · based on 107 candidate reports- 1Recruiter or initial screening call
You start with a screening call to evaluate your background and fit. Prepare to summarize your experience clearly and connect it to the role requirements, since multiple reports and topic prominence emphasize communication and problem solving.
- 2Online assessment or online coding assessment
You may complete an online assessment gate that can include multiple choice plus coding, or coding-only challenges. Reports describe timed work with coding problems submitted without back-and-forth, and one report mentions a 90-minute OA with multiple coding questions.
- 3Technical interviews, potentially multi-round, including panels
You will likely go through one or more technical interviews, and the process may include panels or multi-round discussions. Candidate reports describe live coding problems focused on DSA patterns, sometimes alongside behavioral conversation, and technical discussions that can include system design or code review style reasoning.
- 4Leadership or HR screening panel (if applicable)
Some roles include an HR screening or leadership panel interview to assess leadership capability and cultural fit. The topic data also emphasizes communication and stakeholder communication, so expect questions that probe how you work with others and present your decisions clearly.
What Expedia (IT) actually tests for
How prominent each skill is across reported loopsFind the guide for your role
This is your next step: open the guide for the role you are interviewing for. Each one carries the questions Expedia (IT) interviewers actually ask that position, the loop structure, and pay by level.
Real interview experiences
What candidates said about the loop, difficulty, and outcomes, straight from recent reports for these roles.
What Expedia (IT) pays, by level
Estimated total compensation: base salary plus stock and annual cash bonus.
What separates offers from rejections
Patterns from candidates who got offers, and the mistakes that most often sink a loop.
Do this
- For every coding problem, talk through your approach before you write code, then keep explaining your choices while you implement. Multiple reports describe thinking aloud plus implementation, and the topic set emphasizes problem solving and documenting analytical steps.
- Prepare DSA-style patterns in depth, because Data Structures and Algorithms are the top two topic categories in prominence, and multiple reports describe tight, repeated algorithm sessions. Practice the core transformations, not just one-off solutions.
- If you are interviewing for an ML or Data Engineering adjacent role, be ready for Feature Engineering and Data Pipelines, and for Model Evaluation in ML-oriented topics. Even when the format changes, those topics remain prominent in the extraction.
- Treat system design and technical discussions as tradeoff discussions, not table naming. Candidate reports that mention system design focus on modeling and tradeoffs, so practice explaining your entity or data modeling decisions clearly.
Avoid this
- Do not under-communicate. The topic extraction shows communication skills and stakeholder communication as top prominence, and reports describe behavioral portions and collaborative thinking expectations.
- Do not rely on a single interview format. Some loops include OA style assessments, some include live coding plus behavioral, and some include system design or code review without writing, so you need to adapt on the fly.
- Do not assume the hardest step is the only gate. The extracted data includes multiple coding and technical assessment formats, including online timed OA and online coding assessments, and the overall offer rate is low, so consistency across rounds matters.
- Do not skip documentation and structure in your answers. The extracted topics explicitly include documenting analytical steps and technical interview preparation, and at least one report emphasizes code quality expectations in the OA-style gate.
Expedia (IT) interview FAQ
Answered from real candidate and workplace dataHow hard are the interviews here?
Across 107 candidate reports, 75.9% of the difficulty is medium, 10.8% is hard, 12.0% is easy, and 1.2% is very hard. The topic prominence is also heavily weighted toward foundational skills like Data Structures, Algorithms, Machine Learning fundamentals, and Data Engineering.
What parts of the interview show up the most?
From the extracted topic data, the most prominent categories are Data Structures and Algorithms, Machine Learning fundamentals, Communication skills, Stakeholder communication, and Documenting analytical steps. Coding is reinforced by topics like Python and coding assessments, and you should also expect problem solving to be present.
Is there an online assessment, and what is it like?
Yes, multiple process steps in the data include Online Assessment and Online Coding Assessment, and they are described as coding-focused gates. Candidate reports mention timed OAs with multiple choice sections and coding challenges, and at least one report describes a 90-minute OA with three coding questions.
How should I balance technical and behavioral preparation?
The topic extraction repeatedly includes communication skills and stakeholder communication, and candidate reports describe behavioral conversation segments alongside technical work. Prepare STAR-style stories for behavioral prompts and keep communicating your reasoning during coding so both parts are strong.
Do people get to system design or is it mostly coding?
System design discussions can appear as part of the technical interviews, and the topic set does not list a separate system design category, but candidate reports include system design modeling and tradeoffs. Plan for a mix: DSA and coding first, then discussions that require explanation of structure and design choices.
If I get rejected, can I reapply?
The supplied data does not mention a reapplication policy. If you want, tell me which role you are targeting, and I can suggest what to change based on the topics that are most prominent for that role type.
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