Iphipi

Role: Software Engineer

College: Not Specified

Interview Date: Not Specified (Article published August 22, 2025)

Interview Type: Full-Time

Result: Rejected

Difficulty: Not Specified

Rounds: 4 rounds

Topics Asked: JavaScript Basics, Async/Await, Promises, API Rate Limiting, Algorithms, Data Structures, System Design (scaling, reliability, metrics, alerting)

Experience:

This candidate interviewed for a Software Engineer position at Snabbit. The process included four rounds focusing on technical skills and system design.

Round 1: Warmup + JS Basics (30 min)

This was a relaxed round with a warm-up coding task. Questions included "Tell me about yourself and why Snabbit?", "Explain how you fetch paginated data in JS, what if we want infinite scroll? Follow up: what if API rate limit is hit in between, how do you handle gracefully?", and "Difference between async/await and Promises?".

Round 2: Coding Problem Solving (1 hour)

This round involved a mix of algorithmic and real-world problems. Tasks included writing a function to group incoming bookings by 5-minute slots and count each slot (with a follow-up on handling bookings across multiple timezones for normalization), merging two sorted lists of time ranges (like schedules) while removing overlaps, and assigning the minimum number of technicians needed if one technician can do a maximum of two jobs, given task durations.

Round 3: Not specified as a distinct round, but technical depth was assessed throughout.

Round 4: Domain Specific + Scaling

This round was specific to Snabbit's domain. Questions included "How to measure reliability of field experts? late arrivals?", "What metrics track service quality?", "Follow-up: suppose rating dips suddenly, what alerting system would you set up?", and "If tasks volume doubles suddenly, how do you still keep UI fast?".

Verdict: The candidate was not selected. The feedback indicated solid coding and practical thinking, but suggested that system scaling and edge case depth could be stronger. The interviewer mentioned that "they wanted deeper scaling brain… like low latency tricks and metrics pipelines."