Intermediate–advanced (window functions, optimization) over bookings/clickstream
Out loud, in order: clarify, build it, check it, explain it.
Practise SQLLoadingone moment…
Data engineering interview · Commerce, Travel & Marketplaces
Deep Spark internals (OOM, optimized joins, skew + salting), dimensional modeling, and batch+streaming (Spark+Kafka) design.
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And what its data engineers work with.
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Stages in the order candidates meet them.
4 stages. 4 rounds have reported questions, described below.
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The topics it covers and the questions candidates reported.
1 reported question. See them below
central
High confidence4 reported questions. See them below
1 reported question. See them below
2 reported questions. See them below
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By round. Questions marked Expected are written from the company's standards.
SQLMedium confidence
PySpark / SparkHigh confidence
DSAMedium confidence
Data Modeling / LLDMedium confidence
Nobody reported these exact questions at Expedia. They are the questions a loop for each of its top topics is known to ask, so prepare for them as likely, not as confirmed.
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Ranked by how much of the evidence points at each topic.
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Do the first group before the second.
Spark internals (OOM, optimize app, optimized joins, skew + salting); PySpark
Do first (3)SQL window functions
Batch+streaming design (Spark+Kafka)
DSA (arrays); dimensional modeling (product sense)
ThenLLD/OOP
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Why candidates were turned down, as reported.
Weak Spark internals (skew/OOM/joins)
SQL is named in 37 of 50 company accounts.Shallow dimensional modeling
Modeling is named in 14 of 50 company accounts.No trade-off reasoning in design
Design is named in 27 of 50 company accounts.08
5 reported. Each opens and closes. Composites are labelled.
An online test in Python and SQL, a hiring manager round, then an onsite of four rounds with pair coding. Spark came up a lot: fixing out-of-memory errors, tuning an app, better joins, skew and salting. There was also a missing-number style problem, dimensional modeling and object-oriented design.
What to take from it Practise Spark tuning in detail, especially skew and memory.
A recruiter call about fit, expected pay and notice period. Then a coding test in Python and SQL, a hiring manager interview, and an onsite of four rounds plus a pair-coding test.
What to take from it Have your pay and notice period ready for the first call.
In Austin, two senior data engineers asked many big data questions on Spark, Hadoop and Hive, with no coding in the first round. A 2019 report from Bellevue had mostly definition questions, which the candidate found stressful.
What to take from it Know the basic definitions in plain words.
In Bengaluru in November 2021: a low-level design round on object-oriented ideas and writing classes, a medium LeetCode coding round and a manager round.
What to take from it Practise writing clean classes.
A 2026 review reports behavioral questions about a time you used AI in your work, and about how you handled a challenge.
What to take from it Have a real example of using AI in your work.
Strong first-hand signal; deep Spark internals + dimensional modeling decide senior outcomes.
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Their reported questions, one at a time, against a stopwatch.
Intermediate–advanced (window functions, optimization) over bookings/clickstream
Out loud, in order: clarify, build it, check it, explain it.
Practise SQL10
Pick your level and the weeks you have.
Built from what Expedia asks, strongest first. For the wider basics at your level, follow the Mid level plan alongside it.
Spark and big data
Read: Spark chaptersDrill: Spark playgroundSay it aloud: Spark questionsFull plan: Ace the Spark round
Pipeline and system design
Read: Data pipeline chaptersDrill: Pipeline practiceSay it aloud: Data pipeline questionsFull plan: Ace the pipeline round
Data modeling
Read: Data modeling chaptersDrill: Modeling practiceSay it aloud: Data modeling questionsFull plan: Ace the modeling round
Cloud and tools
Rehearse the Expedia loop
Run the question deckThen repeat your weakest topic once more.