Expedia Group Data Analyst interview questions & guide 2026

The questions you will encounter during the Expedia Group interview process are designed to evaluate your technical competency, logical reasoning, and cultural alignment. The following questions are representative of what past candidates have experienced across various global offices. They are grouped by category to help you identify patterns and structure your preparation effectively.

Behavioral & Motivation

These questions assess your interest in the travel industry, your alignment with company values, and how you manage professional challenges.

• Why do you want to work at Expedia Group, and why are you interested in this specific role?
• Describe a time when you had to work with a difficult stakeholder. How did you resolve the conflict and deliver results?

Preparing for an interview at Expedia Group requires a balanced approach that addresses both your technical execution and your communication style. Interviewers want to see how you think, not just what tools you know.

Role-Related Knowledge – You must demonstrate a strong command of SQL, basic statistics, and data visualization principles. Be prepared to explain the "why" behind your technical choices, such as why you chose a specific statistical test or how you optimized a slow-running query.

Problem-Solving Ability – Expedia Group values structured thinking. When presented with ambiguous business cases, avoid jumping straight to a solution; instead, break the problem down systematically, state your assumptions clearly, and walk your interviewer through your logical framework.

Leadership & Collaboration – Data analysts do not work in isolation. You will be evaluated on your ability to partner with product managers, engineers, and business leaders, translating complex technical findings into simple, actionable recommendations.

Culture Fit & Values – Ensure you understand Expedia Group's mission to power global travel for everyone, everywhere. Be ready to share examples of how you have embraced feedback, demonstrated curiosity, and navigated ambiguity in your previous roles.

The hiring process for a Data Analyst at Expedia Group typically spans three to five weeks, depending on the seniority of the role and the location. The company aims for a structured, transparent evaluation process that balances automated assessments with deep human interaction.

The initial stages focus heavily on screening your foundational skills and cultural indicators. This is often done through automated platforms to ensure objective benchmarking. As you progress, the interviews transition into highly interactive sessions with hiring managers and cross-functional team members, focusing on live technical problem-solving and deep behavioral dives.

The overall process is designed to be rigorous but fair, ensuring that successful candidates possess both the technical capability to handle scale and the interpersonal skills to drive cross-functional alignment.

This visual timeline outlines the standard progression from your initial application to the final offer stage. You should interpret this as a general roadmap; while the core technical and behavioral evaluations remain consistent, early-career positions may place heavier emphasis on numerical assessments, whereas senior roles often feature longer live coding sessions and complex case studies. Use this timeline to pace your preparation, focusing first on core technical skills and automated test formats before refining your live presentation and behavioral storytelling skills.

To excel in the Expedia Group interview process, you must understand exactly what the hiring team is looking for in each core assessment phase.

SQL and Data Manipulation (Live Coding)

The live coding round is a critical hurdle where you will work through data manipulation problems in real-time with an engineering or analytics manager. This round evaluates your technical fluency, query efficiency, and how you handle live feedback.

Be ready to go over:

• Complex Joins and Aggregations – Combining multiple transactional tables (e.g., users, searches, bookings) using appropriate join types and groupings.
• Window Functions – Utilizing functions like LEAD, LAG, RANK, and SUM() OVER to analyze sequential user behavior.
• Query Optimization – Writing clean, readable code and understanding how to structure queries to run efficiently over massive datasets.
• Advanced concepts (less common) – Common Table Expressions (CTEs), subqueries versus temporary tables, and handling null values in mathematical computations.

Example scenarios:

• "Write a query to calculate the month-over-month growth rate in hotel bookings for users based in the United States."
• "Find the average time elapsed between a user's first search and their actual flight booking on the platform."
• "Identify users who searched for a hotel room but booked a different hotel in the same city within a 24-hour window."

Product & Business Metrics (Flight Booking Case Studies)

In this area, interviewers evaluate your product sense and how you apply analytical frameworks to travel-specific business problems. They want to see if you can connect data patterns to actual user experiences and business outcomes.

Be ready to go over:

• A/B Testing Methodology – Designing experiments, defining control and variant groups, choosing primary metrics, and understanding sample size and statistical power.
• Funnel Analysis – Identifying drop-offs in the multi-step travel booking flow (search -> select -> details -> payment -> confirmation).
• KPI Definition – Selecting the right metrics to measure product health, such as Conversion Rate, Average Booking Value (ABV), and Customer Lifetime Value (CLV).
• Advanced concepts (less common) – Cohort analysis for repeat travelers, understanding the impact of external search engines on organic traffic attribution, and network effects in travel supply.

Example scenarios:

• "We are launching a new layout for our flight search results page. How would you design the experiment and measure success?"
• "A product manager wants to add a 'frequently booked together' recommendation widget. What metrics would you track to evaluate if this feature is successful or if it cannibalizes other high-margin products?"
• "Hotel search conversions have dropped by 5% this week in Europe. Walk me through your diagnostic dashboard to find out why."

Strengths-Based & Behavioral Assessments (Hirevue / Video Rounds)

Often utilized as an early screening tool, these assessments measure your behavioral alignment, communication clarity, and situational judgment.

Be ready to go over:

• Motivation and Interest – Clearly articulating why you want to work specifically in travel tech at Expedia Group.
• Overcoming Obstacles – Describing how you handle shifting priorities, tight deadlines, or missing project requirements.
• Collaboration – Explaining how you partner with non-technical stakeholders to drive data adoption.
• Advanced concepts (less common) – Explaining a complex technical project you completed to an audience with no data background.

Example scenarios:

• "Why are you interested in this specific internship/role, and what unique strengths will you bring to our team?"
• "Tell me about a time when you discovered an error in your analysis after sharing the results with a stakeholder. What did you do?"
• "Describe a situation where you had to persuade a product team to change their strategy based entirely on your data insights."

As a Data Analyst at Expedia Group, your day-to-day responsibilities will be highly dynamic and centered around driving product and business growth through data. You will spend a significant portion of your time translating raw database tables into structured, intuitive analytical assets. This involves writing optimized SQL queries, building interactive Tableau or PowerBI dashboards, and maintaining data pipelines that enable business teams to self-serve their reporting needs.

Beyond technical execution, you will serve as a strategic consultant to your product and engineering partners. You will actively participate in sprint planning, product reviews, and roadmap discussions. For example, when a product manager proposes a new feature for the Vrbo mobile app, you will be responsible for defining the experiment framework, monitoring the live user data, and presenting the final performance analysis to determine if the feature should be fully rolled out.

You will also be tasked with proactive exploratory analysis. Instead of just answering questions posed by stakeholders, you will dive into user clickstream data to uncover hidden friction points, discover emerging travel trends, or identify opportunities for cost savings. Your ability to connect disparate data points and tell a cohesive story with data is what will ultimately drive business impact and influence product strategy.

To be competitive for the Data Analyst position at Expedia Group, you must demonstrate a strong blend of technical expertise, analytical intuition, and communication skills.

• Must-have technical skills – High proficiency in SQL (writing complex joins, aggregations, and window functions) and experience with a major data visualization tool such as Tableau, PowerBI, or Looker.
• Must-have analytical skills – Solid understanding of basic statistics, hypothesis testing, and standard A/B testing methodologies.
• Nice-to-have skills – Proficiency in Python or R for data manipulation, statistical analysis, and automated reporting. Experience working with cloud data warehouses like Snowflake, Teradata, or AWS Athena.
• Experience level – Typically requires a bachelor's degree in a quantitative field (e.g., Statistics, Mathematics, Computer Science, Economics) and 1–3 years of experience in an analytical role. For early-career or internship positions, strong academic project experience and quantitative test performance are highly valued.
• Soft skills – Outstanding verbal and written communication, a proactive approach to problem-solving, and the ability to work collaboratively in a fast-paced, highly matrixed global organization.

Q: How technical is the Data Analyst interview process at Expedia Group? A: The process is moderately technical. You are expected to have a strong command of SQL and product metrics. Senior roles will feature a live coding assessment, while entry-level roles may rely more on timed numerical tests and automated video screens.

Q: What is the typical timeline from application to offer? A: The timeline generally ranges from three to five weeks. However, candidates have occasionally reported communication delays during high-volume hiring seasons. Being proactive and maintaining open communication with your recruiter is highly recommended.

Q: Can I choose between SQL, Python, or R during the live coding round? A: For most Data Analyst positions, SQL is the primary language evaluated during the live coding round, as it is the foundation of the daily workflow. If the role has a heavy predictive modeling focus, you may also be asked to solve problems using Python or R.

Q: How should I prepare for the timed numerical and logical tests? A: Focus on practicing speed-based math, data interpretation, and pattern recognition. Refresh your ability to quickly read charts, calculate percentages, and interpret financial or operational tables under strict time limits.

Q: What is the hybrid work policy at Expedia Group? A: Expedia Group generally operates on a hybrid model, requiring employees to spend a set number of days per week in their local office (such as London, Seattle, or Gurgaon) to foster collaboration and team cohesion.

To maximize your chances of success, keep these practical, insider tips in mind as you navigate the interview process:

• Master the STAR Method: For all behavioral and Hirevue questions, structure your answers using the Situation, Task, Action, and Result framework. Focus heavily on your specific actions and quantify the results whenever possible (e.g., "This analysis resulted in a 4% increase in checkout conversion").

• Brush up on Travel Industry Metrics: Familiarize yourself with standard travel and e-commerce KPIs. Understand the relationship between search volume, click-through rate, conversion rate, cancellation rate, and average order value.
• Practice Live SQL Coding Out Loud: During the live coding round, do not code in silence. Talk through your logic as you write the query. This allows the interviewer to understand your problem-solving process and offer helpful hints if you get stuck.
• Prepare Questions for Your Interviewers: Show your product curiosity by asking thoughtful questions at the end of your live rounds. Ask about the specific data challenges their team is currently facing, how they handle data quality at scale, or how they collaborate with product managers.

Securing a Data Analyst role at Expedia Group is an exceptional opportunity to work at the forefront of travel technology. The role offers a unique combination of technical challenge, massive scale, and direct business impact. By mastering SQL, refining your product sense, and practicing structured communication, you can stand out as a highly competitive candidate.

As you prepare, focus on building a balanced study plan. Dedicate time to writing clean SQL queries, studying A/B testing frameworks, and practicing your behavioral stories. Remember that confidence and clarity in your communication are just as important as your technical execution. For more detailed company insights, salary data, and practice questions, be sure to explore the resources available on Dataford.

This compensation data represents the typical salary range for a Data Analyst at Expedia Group. When evaluating an offer, keep in mind that total compensation often includes a base salary, performance bonuses, and equity components. Seniority, location, and specialized technical skills can significantly influence your final package, so use this data as a benchmark for your negotiations.