Paytm's data-engineering rounds probe multi-rail ingestion, rolling analytics, and operational data quality across a broad payments and commerce business.
In 2026 expect a pipeline round on consolidating transaction data across wallet, UPI, and cards into a unified warehouse table (reconciling differing schemas and late data), a SQL round on rolling active-user counts made incremental, and a data-quality round on preventing a broken upstream feed from silently corrupting revenue dashboards. Interviewers reward engineers who reason about schema unification, late-data handling, incremental computation, and circuit-breaking data-quality gates rather than one-off batch jobs. Ground answers in real payment-rail reconciliation.
About Paytm
Listed Indian fintech offering UPI, payments, lending (consumer + merchant), and a payments bank.
Recruiter screen and technical pre-screen
SQL and data-manipulation round
Multi-source ingestion and pipeline design round
Hiring-manager and behavioural round, then offer
Round 1 (45-60 min)
SQL round on rolling-window and incremental analytics.
Round 2 (60 min)
ingestion pipeline round on multi-rail schema unification.
Round 3 (45-60 min)
data-quality and reliability round.
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.