Expedia Interview Questions — Page 2

Expedia·Software Engineer·Technical Phone Screen

May 2026

Expedia software engineer interview focused almost entirely on how I use AI coding tools day to day. Less of a technical screen and more of a conversation about habits, workflows, and risk awareness. Felt more like a product feedback session than an interview, which was a weird vibe.

Do you use AI coding assistants at work, and if so, what kinds of tasks do you use them for and how frequently?
Walk me through your typical workflow when using an AI coding tool, from writing a prompt to getting code into a pull request.
What concrete benefits have you seen from using AI coding tools, whether around speed, code quality, learning, or something else?
What risks do you actively watch for when working with AI-generated code, things like hallucinations, security issues, IP concerns, or over-reliance?
How do you actually mitigate those risks in your day-to-day work rather than just being aware of them?
If you could change something about AI coding tools, whether the product itself, how teams use them, or the guardrails around them, what would you improve?

“Pretty open-ended opener.”

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Expedia·Software Engineer·Technical Phone Screen

May 2026

Expedia software engineer interview that was basically a deep project walkthrough. They pick something from your resume and just... go in. Be ready to talk specifics.

Walk me through a project on your resume in detail: what was the problem, what did you design, what alternatives did you consider, what was your specific contribution versus the team's, what trade-offs did you make, what issues came up and how did you resolve them, and what was the final measurable impact?

“This is the whole interview basically.”

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Expedia·Software Engineer·Onsite - System Design / Architecture

May 2026

System design round at Expedia for a software engineer role. The main problem was designing a synchronous order cancellation and refund processor, which sounds straightforward until you get into the weeds of distributed state and partial failures. Pretty intense for a single question but they clearly wanted depth.

Design a synchronous order cancellation and refund processor. The API must return a definitive success or failure only after the cancellation and refund are fully resolved, not fire-and-forget. Cover order state validation, payment gateway integration, atomic state updates across order/payment/inventory, partial failure handling, idempotency, distributed transactions vs compensation-based approaches, and timeout/circuit breaker patterns.

“This took up the entire session.”

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Expedia·Software Engineer·Onsite - Coding / Algorithms

May 2026

Expedia coding round, one algorithmic problem that looked manageable until I actually had to implement it efficiently. The substring palindrome anagram counting problem sounds straightforward but the naive approach is way too slow and they clearly wanted the bitmask trick.

Given a list of strings, for each string count how many substrings can be rearranged to form a palindrome.

“My first instinct was brute force: enumerate all substrings, count character frequencies, check if at most one character has an odd count.”

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Expedia·Technical Program Manager·Technical Phone Screen

May 2026

Interviewed for a TPM role at Expedia, got asked about Agile fundamentals which felt like a warmup question but still managed to second-guess myself halfway through.

Can you explain Agile methodology and walk through its core principles?

“Seemed straightforward but I over-rotated into process details and forgot to tie it back to outcomes.”

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Expedia·Software Engineer·Technical Phone Screen

May 2026

Expedia software engineer interview where they drop a big JSON blob in the editor and tell you to do something with it. Sounds easy but the real conversation is about everything around the parsing, not the parsing itself.

You're given a large JSON string in the editor. Write code to parse it and extract specific fields from it. You can use any language or library you want.
Once you've parsed the JSON, how would you model the data in your code? Walk through your reasoning between typed DTO classes versus keeping things as raw maps.
How do you handle missing fields, optional values, and type mismatches when deserializing JSON?
Can you explain streaming JSON parsers and when you'd choose a streaming approach over full deserialization?
How would you write a JSON parser from scratch? Describe the approach and what the time and space complexity would look like.
How would you test the JSON extraction logic you just wrote?

“The open-ended part threw me a bit.”

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Expedia·Software Engineer·Onsite - System Design / Architecture

May 2026

System design round at Expedia for a software engineer role, centered entirely on designing a connectivity service that sits between external partners and an internal validation system. Pretty deep dive, they wanted actual HTTP specs not just hand-wavy architecture talk.

Design a REST API for a connectivity service that lets external partners create or update listings on your platform, including endpoint design, request/response payloads, required headers, authentication, and idempotency strategy.
Walk through the end-to-end flow from a partner sending a listing request to your service, through to the internal validation/domain service, and back to the partner with a result.
How would you handle partner retries safely to avoid creating duplicate listings?
How does your service stay resilient when the internal validation/domain service is slow or unavailable?
What HTTP status codes would your API return, and under what conditions would each apply?
How would you design observability into this service, covering metrics, logging, and distributed tracing?

“This is where I spent most of my time and honestly felt like I was playing catch-up.”

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Expedia·Software Engineer·Onsite - System Design / Architecture

May 2026

System design round at Expedia focused entirely on building a disaster notification system for a vacation rental platform. Pretty intense scope for a single session, lots of moving parts to juggle.

Design a natural disaster notification system for a vacation rental platform. The system receives disaster events from a third-party API with affected geographic regions, and must identify and notify all impacted properties, orders, hosts, and guests in a timely manner. Walk through your data modeling approach, geospatial indexing strategy, query path, freshness requirements, and how you'd handle many concurrent disaster events at scale.

“I started with the naive approach, just querying all active orders and filtering by location, and the interviewer let me dig myself into that hole for a bit before nudging me toward geospatial indexing.”

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Expedia·Software Engineer·Hiring Manager Screen

May 2026

Behavioral hiring manager screen for a software engineer role at Expedia. Three questions, pretty standard territory except question three which has a specific angle that'll trip you up if you're not ready for it.

Why do you want to work at Expedia, and why this particular team?
What project are you most proud of, and what was your specific contribution to it?
How do you hold yourself accountable on a team? Specifically, how do you keep projects on track and what do you do when someone else is blocking your progress?

“Pretty expected opener.”

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Expedia·Data Scientist·Technical Phone Screen

May 2026

Deep technical interview for a Data Scientist role at Expedia focused entirely on ML evaluation and deployment for a hotel ranking model. One long multi-part question that covers basically everything from offline metrics to production monitoring. Felt more like a system design session than a typical DS interview.

How would you design an offline evaluation plan for a hotel ranking model that avoids data leakage, accounts for position bias, and validates that conversion probability predictions are well-calibrated?
Which ranking metrics would you report for this model, and can you explain the formulas and why they reflect actual business value rather than just model performance?
How would you identify the key drivers of model predictions without leaking target information into your feature analysis?
Walk through how you'd roll out this ranking model safely, including shadow mode, canary deployments, guardrail alarms, drift detection, and an automatic rollback policy.
How would you verify that improving a surrogate objective offline actually translates to gains on the real business KPI, and what would you do if the offline-to-online relationship breaks down?

“This is where I spent the most time.”

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