PhonePe's data-engineering rounds are payment-stream native and correctness-obsessed.
In 2026 expect a pipeline round on computing daily per-merchant settlement summaries from a high-volume UPI transaction stream with exactly-once guarantees, a SQL round on payment-health monitoring (merchants whose success rate drops below a threshold, conditional aggregation, partitioned by state), and a feature-engineering round on low-latency rolling per-user fraud signals. Because money is involved, interviewers weight idempotency, deduplication, and reconciliation against the ledger over generic ETL. Ground every answer in real UPI settlement and fraud-scoring workflows, and be precise about how you avoid double-counting.
About PhonePe
India's largest UPI app by volume; also offers insurance, mutual funds, gold, and merchant payments.
Recruiter screen and technical pre-screen
SQL and data-manipulation round
Payment-stream pipeline and feature-engineering round
Hiring-manager and behavioural round, then offer
Round 1 (45-60 min)
SQL round on conditional aggregation and payment-health metrics.
Round 2 (60 min)
pipeline design round on exactly-once settlement aggregation.
Round 3 (45-60 min)
fraud feature-engineering round with rolling windows.
Round 4 (45 min)
behavioural and hiring-manager round.
Sourced from 2+ candidate post-mortems. Hit Practice to answer any one with AI voice feedback.
The typical PhonePe recruitment process has 4 stages: Recruiter screen and technical pre-screen → SQL and data-manipulation round → Payment-stream pipeline and feature-engineering round → Hiring-manager and behavioural round, then offer.
PhonePe typically conducts 4 interview rounds: Round 1 (45-60 min): SQL round on conditional aggregation and payment-health metrics.; Round 2 (60 min): pipeline design round on exactly-once settlement aggregation.; Round 3 (45-60 min): fraud feature-engineering round with rolling windows.; Round 4 (45 min): behavioural and hiring-manager round..
HireStepX recommends the Exactly-Once-and-Reconciled framework for this type of interview: Guarantee exactly-once aggregation over payment streams with idempotency and dedup, monitor payment health in SQL, and engineer low-latency fraud features
To answer this question well, HireStepX recommends the Exactly-Once-and-Reconciled approach: Guarantee exactly-once aggregation over payment streams with idempotency and dedup, monitor payment health in SQL, and engineer low-latency fraud features Ground your answer in a specific real example from your own experience.
To answer this question well, HireStepX recommends the Exactly-Once-and-Reconciled approach: Guarantee exactly-once aggregation over payment streams with idempotency and dedup, monitor payment health in SQL, and engineer low-latency fraud features Ground your answer in a specific real example from your own experience.
To answer this question well, HireStepX recommends the Exactly-Once-and-Reconciled approach: Guarantee exactly-once aggregation over payment streams with idempotency and dedup, monitor payment health in SQL, and engineer low-latency fraud features Ground your answer in a specific real example from your own experience.
To answer this question well, HireStepX recommends the Exactly-Once-and-Reconciled approach: Guarantee exactly-once aggregation over payment streams with idempotency and dedup, monitor payment health in SQL, and engineer low-latency fraud features Ground your answer in a specific real example from your own experience.
To answer this question well, HireStepX recommends the Exactly-Once-and-Reconciled approach: Guarantee exactly-once aggregation over payment streams with idempotency and dedup, monitor payment health in SQL, and engineer low-latency fraud features Ground your answer in a specific real example from your own experience.