Swiggy's data-engineering rounds mix stream processing, analytical SQL, and experimentation pipelines, reflecting a food-delivery business run on real-time signals.
In 2026 expect a streaming round on producing per-restaurant delivery-time analytics from order and GPS event streams (joining streams with different arrival rates, event-time processing), a SQL round on week-over-week order-volume drops using window functions with LAG, and an experimentation round on building reliable A/B metric pipelines that guard against sample-ratio mismatch and peeking. Swiggy is experimentation-heavy, so interviewers reward statistically sound aggregation and correct stream-stream joins over generic batch ETL. Ground answers in real delivery workflows.
About Swiggy
Listed Indian food-delivery + quick-commerce (Instamart) platform, also operates dine-out (Dineout) and B2B grocery.
Recruiter screen and technical pre-screen
SQL and data-manipulation round
Streaming pipeline and experimentation design round
Hiring-manager and behavioural round, then offer
Round 1 (45-60 min)
SQL round on window functions and trend detection.
Round 2 (60 min)
streaming pipeline design round with stream-stream joins.
Round 3 (45-60 min)
experimentation and A/B metric pipeline round.
Round 4 (45 min)
behavioural and hiring-manager round.
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