Find the top 5 selling products per category for the last month
Out loud, in order: clarify, build it, check it, explain it.
Practise SQLLoadingone moment…
Data engineering interview · Commerce, Travel & Marketplaces
DSA + SQL, then a Spark-heavy round (OOM, partitionBy vs bucketBy) and a Staff-DE system-design finale.
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And what its data engineers work with.
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Stages in the order candidates meet them.
6 stages. 3 rounds have reported questions, described below.
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The topics it covers and the questions candidates reported.
2 reported questions. See them below
1 reported question. See them below
central
High confidence3 reported questions. See them below
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By round. Questions marked Expected are written from the company's standards.
SQLHigh confidence
DSA / PythonMedium confidence
SparkHigh confidence
Nobody reported these exact questions at Walmart. 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 fixes, partitionBy vs bucketBy, skew, PySpark)
Do first (3)SQL (top-N per group, window, joins, optimization)
System design (real-time clickstream, event-driven); DSA medium–hard
Kafka
ThenData modeling/warehousing
Behavioral
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Why candidates were turned down, as reported.
Shallow Spark internals (OOM, partitionBy vs bucketBy)
Spark is named in 25 of 50 company accounts.Weak system design at Staff round
Design is named in 27 of 50 company accounts.Cannot translate business logic to efficient SQL
SQL is named in 37 of 50 company accounts.DSA misses in Tech 1
Python is named in 13 of 50 company accounts.08
4 reported, 1 composite. Each opens and closes. Composites are labelled.
A recruiter call, a first technical round (data structures, two SQL questions with windows, joins and tuning, and PySpark), a second technical round (Spark tuning, fixing memory errors, partitionBy against bucketBy, Kafka, design), a final staff-level round on event-driven design (about 1 hour 45 minutes) and HR. Real questions: top 5 products per category, a Spark out-of-memory fix, and a design for a Walmart.com clickstream pipeline.
What to take from it Know Spark tuning and be ready for a long design round.
In Bentonville in December 2025: a recruiter screen about personality fit and STAR stories, then a technical round on processing large data.
What to take from it Prepare STAR stories before the first call.
Reported topics: SQL tuning and data modeling, Spark and PySpark tuning, Kafka, and a hiring manager round on past projects. The first screen is a HackerRank test with two SQL problems and one data structures question.
What to take from it Practise SQL tuning and one data structures question.
One candidate had Spark coding and Azure questions. Another says the team wants real algorithm skill, with topics such as red-black trees.
What to take from it Check the team: some want deeper algorithms.
Composite walkthroughs. Built from the company's documented loop, not from one person's account.
This is a composite, not one person's account. It is built from the loop we have on record for Walmart. Questions reported for this round: Find the top 5 selling products per category for the last month; Window functions, joins (inner/outer/cross), aggregations, performance tuning.
What to take from it Practise these questions before you reach this round.
Strong first-hand signal; Spark depth + system design decide it, with a Staff-DE design finale.
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Their reported questions, one at a time, against a stopwatch.
Find the top 5 selling products per category for the last month
Out loud, in order: clarify, build it, check it, explain it.
Practise SQL10
Pick your level and the weeks you have.
Built from what Walmart 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
Python and coding
Read: Python chaptersDrill: Python practiceSay it aloud: Python questionsFull plan: Ace the Python round
Cloud and tools
Pipeline and system design
Read: Data pipeline chaptersDrill: Pipeline practiceSay it aloud: Data pipeline questionsFull plan: Ace the pipeline round
Behavioral and communication
Read: Behavioral storytellingSay it aloud: Behavioral questions
Rehearse the Walmart loop
Run the question deckThen repeat your weakest topic once more.