CRED's data-engineering rounds probe reproducible feature pipelines, statement-history SQL, and governance-aware design, reflecting a credit-focused fintech handling sensitive financial data.
In 2026 expect a pipeline round on computing per-user creditworthiness features from bureau data, transaction history, and app behaviour with point-in-time correctness for model training, a SQL round on trailing on-time payment ratios over recent statements with careful partial-window handling, and a governance round on enabling analytics and model training while respecting strict PII and financial-data controls. Interviewers reward reasoning about feature reproducibility, point-in-time correctness, tokenisation, and lineage over generic pipelines. Ground answers in real credit-ML and compliance workflows.
About CRED
Premium Indian fintech for credit-card payments + reward platform; expanded into payments, lending, and rent payments.
Recruiter screen and technical pre-screen
SQL and data-manipulation round
Feature pipeline and governance design round
Hiring-manager and behavioural round, then offer
Round 1 (45-60 min)
SQL round on statement-history window functions.
Round 2 (60 min)
feature-pipeline round with point-in-time correctness.
Round 3 (45-60 min)
data-governance and platform design 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.