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Finance, Payments & Fintech

PhonePe

Payments / fintech (India) · Data Engineering interview

Five rounds with a strong low-level/system-design bar (a Shazam-like design) and in-person hiring-manager rounds.

Cloud / platform

Spark, Hadoop, Kafka; on-prem heavy

Reported difficulty

Not reported

SQLSparkLinuxSystem/LLDPython/Java

Hiring process

R1 (SQL 30m + other 30m)

Coding/Linux/SQL

System/LLD

HM ×2 (in person, Bengaluru)

Offer

Round-by-round breakdown

SQL

Medium confidence

30 min SQL coding (R1)
Window functions, dedup, transaction analytics

Coding / Linux

Medium confidence

Coding questions + Linux + SQL

System / Low-Level Design

· strong barMedium confidence

Components: microservices vs monolith, DB choice, caching, SPOF
List APIs, classes, methods w/ signatures, design patterns
Design a Shazam-like system (hashing + sliding window, no ML)

System & pipeline design prompts

Shazam-like audio-fingerprint lookup (hashing + sliding window, hashes in a DB)

Prep — high priority

SQL (timed coding, window functions)
Low-level + system design (components, microservices vs monolith, caching, SPOF, design patterns; hashing/sliding-window)
Linux basics

Prep — medium priority

Spark/big-data internals (verify)
Project deep-dive for HM rounds

Rejection patterns

Weak low-level/system design (APIs/classes/patterns)
Shaky SQL
Thin project depth (probed hard in HM rounds)

Reported experiences

Big Data / SWE

ReportedFirst-hand

5 rounds; R1 = 30 min SQL + 30 min other; coding + Linux + SQL; system/low-level design (microservices vs monolith, DB/caching/SPOF, design patterns; Shazam-like hashing+sliding-window); R4/R5 HM in Bengaluru.

Rehearse for PhonePe

Answered questions on what PhonePe 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…

Finance, Payments & Fintech

PhonePe

Payments / fintech (India) · Data Engineering interview

Five rounds with a strong low-level/system-design bar (a Shazam-like design) and in-person hiring-manager rounds.

Cloud / platform

Spark, Hadoop, Kafka; on-prem heavy

Reported difficulty

Not reported

SQLSparkLinuxSystem/LLDPython/Java

Hiring process

R1 (SQL 30m + other 30m)

Coding/Linux/SQL

System/LLD

HM ×2 (in person, Bengaluru)

Offer

Round-by-round breakdown

SQL

Medium confidence

30 min SQL coding (R1)
Window functions, dedup, transaction analytics

Coding / Linux

Medium confidence

Coding questions + Linux + SQL

System / Low-Level Design

· strong barMedium confidence

Components: microservices vs monolith, DB choice, caching, SPOF
List APIs, classes, methods w/ signatures, design patterns
Design a Shazam-like system (hashing + sliding window, no ML)

System & pipeline design prompts

Shazam-like audio-fingerprint lookup (hashing + sliding window, hashes in a DB)

Prep — high priority

SQL (timed coding, window functions)
Low-level + system design (components, microservices vs monolith, caching, SPOF, design patterns; hashing/sliding-window)
Linux basics

Prep — medium priority

Spark/big-data internals (verify)
Project deep-dive for HM rounds

Rejection patterns

Weak low-level/system design (APIs/classes/patterns)
Shaky SQL
Thin project depth (probed hard in HM rounds)

Reported experiences

Big Data / SWE

ReportedFirst-hand

Rehearse for PhonePe

Answered questions on what PhonePe 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