Free tool · no sign-up · 4 interview rounds
Generate AI-powered Swiggy interview questions for all 4 rounds. Process: Online Assessment → Technical × 2 → System Design → HR.
From our curated bank of 10 Swiggy-specific questions. The generator produces fresh AI-tailored questions each run.
What makes Swiggy's engineering challenges unique compared to other Indian product companies?
Tip: Swiggy operates in real-time: 30-minute delivery windows, live tracking, dynamic pricing, surge detection. Engineering challenges include real-time logistics optimisation, fraud prevention in O(ms), and handling 5× traffic spikes on Fridays. Show you've thought about these constraints when applying.
Design Swiggy's real-time order tracking system.
Tip: Components: delivery partner GPS events via WebSocket/MQTT → Kafka → stream processor (Flink) → state store (Redis) → WebSocket push to user. Challenges: 1M concurrent connections, partner going offline mid-delivery, GPS drift. Use heartbeat + last-known-good position fallback.
How would you build a restaurant ETA prediction system?
Tip: Features: historical prep times per restaurant/dish, current order queue, time of day, weather. Model: gradient boosted trees or a lightweight neural net. Serving: pre-computed p50/p90 per restaurant, updated every 5 min via batch ML pipeline. Online adjustment: real-time signals from kitchen accept/reject events.
What is Apache Kafka and why is it essential for a food delivery platform?
Tip: Kafka: distributed event streaming platform. For Swiggy: order events (placed → accepted → prepared → picked → delivered), payment events, fraud signals all flow through Kafka. Benefits: decouples producers from consumers, allows event replay, high throughput (millions of events/sec). Retention: replay for ML feature generation.
Write code to find the shortest path between a restaurant and a delivery location on a grid.
Tip: BFS on a grid with obstacles (blocked roads). O(rows × cols) time and space. For weighted edges (traffic, road type), use Dijkstra. Swiggy uses graph algorithms with real map data and traffic weights — BFS is the gateway question to test your graph fundamentals.
Practise questions for each stage to maximise your preparation.
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