Cores, executors, jobs, stages; transformations vs actions
Out loud, in order: clarify, build it, check it, explain it.
Practise Apache SparkLoadingone moment…
Data engineering interview · Commerce, Travel & Marketplaces
Databricks/Delta-centric: deep Spark internals (repartition vs coalesce, Z-ordering, incremental loads) and scenario SQL.
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And what its data engineers work with.
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Stages in the order candidates meet them.
5 stages. 3 rounds have reported questions, described below.
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The topics it covers and the questions candidates reported.
central
High confidence4 reported questions. See them below
2 reported questions. See them below
1 reported question. See them below
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By round. Questions marked Expected are written from the company's standards.
SparkHigh confidence
SQLHigh confidence
Databricks + projectMedium confidence
Nobody reported these exact questions at Myntra. 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/Databricks/Delta internals (repartition vs coalesce, Delta vs Parquet, Z-ordering, joins, incremental loads)
Do first (2)Scenario SQL (CTEs, conditional joins, window, nth-highest, rolling avg)
Medallion pipeline design
ThenProject deep-dive
Behavioral
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Why candidates were turned down, as reported.
Shallow Spark/Databricks/Delta internals
Spark is named in 25 of 50 company accounts.Cannot write scenario SQL with CTEs/conditional joins
SQL is named in 37 of 50 company accounts.Weak project depth
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2 reported, 3 composite. Each opens and closes. Composites are labelled.
A deep Spark round: cores, executors, jobs and stages, transformations against actions, repartition against coalesce, Delta against Parquet, Z-ordering, joins and incremental loads with Delta. Also scenario SQL (CTEs, conditional joins), Databricks and a talk about a project.
What to take from it Know how Spark runs a job, and how Delta loads data step by step.
Not a data engineering account. The first round was SQL. The second covered a past project and case-style questions.
What to take from it Even a short loop asks about your projects.
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 Myntra. central. Questions reported for this round: Cores, executors, jobs, stages; transformations vs actions; REPARTITION vs COALESCE; optimization; Delta vs Parquet; Z-Ordering.
What to take from it Practise these questions before you reach this round.
This is a composite, not one person's account. It is built from the loop we have on record for Myntra. Questions reported for this round: Advanced scenario-based SQL with CTEs and conditional joins; Window functions, nth-highest, rolling averages, self joins.
What to take from it Practise these questions before you reach this round.
This is a composite, not one person's account. It is built from the loop we have on record for Myntra. Questions reported for this round: Databricks services usage; past projects, challenges faced.
What to take from it Practise these questions before you reach this round.
Databricks/Delta depth + scenario SQL decide outcomes.
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Their reported questions, one at a time, against a stopwatch.
Cores, executors, jobs, stages; transformations vs actions
Out loud, in order: clarify, build it, check it, explain it.
Practise Apache Spark10
Pick your level and the weeks you have.
Built from what Myntra asks, strongest first. For the wider basics at your level, follow the Mid level plan alongside it.
Cloud and tools
Spark and big data
Read: Spark chaptersDrill: Spark playgroundSay it aloud: Spark questionsFull plan: Ace the Spark round
Behavioral and communication
Read: Behavioral storytellingSay it aloud: Behavioral questions
Rehearse the Myntra loop
Run the question deckThen repeat your weakest topic once more.