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Commerce, Travel & Marketplaces

Myntra

Fashion e-commerce (India) · Data Engineering interview

Databricks/Delta-centric: deep Spark internals (repartition vs coalesce, Z-ordering, incremental loads) and scenario SQL.

Cloud / platform

Databricks; Spark, Delta Lake (Azure/GCP)

Reported difficulty

Not reported

SparkSQLDatabricksDeltaPython

Hiring process

Spark deep-dive

Scenario SQL

Databricks + project

Behavioral

Offer

Round-by-round breakdown

Spark

· centralHigh confidence

Cores, executors, jobs, stages; transformations vs actions
REPARTITION vs COALESCE; optimization
Delta vs Parquet; Z-Ordering
Join strategies; incremental loading using Delta

SQL

High confidence

Advanced scenario-based SQL with CTEs and conditional joins
Window functions, nth-highest, rolling averages, self joins

Databricks + project

Medium confidence

Databricks services usage; past projects, challenges faced

System & pipeline design prompts

E-commerce/supply-chain pipeline on Databricks/Delta (bronze/silver/gold); incremental loads

Prep — high priority

Spark/Databricks/Delta internals (repartition vs coalesce, Delta vs Parquet, Z-ordering, joins, incremental loads)
Scenario SQL (CTEs, conditional joins, window, nth-highest, rolling avg)

Prep — medium priority

Medallion pipeline design
Project deep-dive
Behavioral

Rejection patterns

Shallow Spark/Databricks/Delta internals
Cannot write scenario SQL with CTEs/conditional joins
Weak project depth

Reported experiences

Data Engineer (~3 YoE)

ReportedFirst-hand

Spark deep-dive (cores/executors/jobs/stages, transformations vs actions, repartition vs coalesce, Delta vs Parquet, Z-ordering, joins, incremental loads w/ Delta) + scenario SQL (CTEs, conditional joins) + Databricks + project discussion.

Rehearse for Myntra

Answered questions on what Myntra actually asks — each with the short answer, the answer that gets you rejected, and the follow-up.

Then build one and have it reviewed: design a daily orders pipeline or model a marketplace. No account.

All interview experiences

Openingloading the content…

Commerce, Travel & Marketplaces

Myntra

Fashion e-commerce (India) · Data Engineering interview

Databricks/Delta-centric: deep Spark internals (repartition vs coalesce, Z-ordering, incremental loads) and scenario SQL.

Cloud / platform

Databricks; Spark, Delta Lake (Azure/GCP)

Reported difficulty

Not reported

SparkSQLDatabricksDeltaPython

Hiring process

Spark deep-dive

Scenario SQL

Databricks + project

Behavioral

Offer

Round-by-round breakdown

Spark

· centralHigh confidence

Cores, executors, jobs, stages; transformations vs actions
REPARTITION vs COALESCE; optimization
Delta vs Parquet; Z-Ordering
Join strategies; incremental loading using Delta

SQL

High confidence

Advanced scenario-based SQL with CTEs and conditional joins
Window functions, nth-highest, rolling averages, self joins

Databricks + project

Medium confidence

Databricks services usage; past projects, challenges faced

System & pipeline design prompts

E-commerce/supply-chain pipeline on Databricks/Delta (bronze/silver/gold); incremental loads

Prep — high priority

Spark/Databricks/Delta internals (repartition vs coalesce, Delta vs Parquet, Z-ordering, joins, incremental loads)
Scenario SQL (CTEs, conditional joins, window, nth-highest, rolling avg)

Prep — medium priority

Medallion pipeline design
Project deep-dive
Behavioral

Rejection patterns

Shallow Spark/Databricks/Delta internals
Cannot write scenario SQL with CTEs/conditional joins
Weak project depth

Reported experiences

Data Engineer (~3 YoE)

ReportedFirst-hand

Rehearse for Myntra

Answered questions on what Myntra actually asks — each with the short answer, the answer that gets you rejected, and the follow-up.

Then build one and have it reviewed: design a daily orders pipeline or model a marketplace. No account.

All interview experiences