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Summary
I interviewed for an SDE 2 position at GoDaddy in Pune (Remote) in March 2025 and received an offer after 3 rounds covering behavioral, frontend (React), and backend (API Design).
Full Experience
Current Status
Company: Startup Position: SDE 2 Location: Remote Current YOE: 3.5 yrs
Interview Details
Company: GoDaddy Position: SDE 2 Rounds: 3 (Behavioral + 2 Technical) Location: Pune (my team will be wokring remote)
Round 1: Behavioral + Culture Fit (30-45 mins)
A discussion with the Hiring Manager about:
- Background & past experience
- Team culture & collaboration
- Challenges faced in previous roles
Round 2: Technical 1 (React + Frontend) (1 hour)
Problem: Build a Movie Search Page in React.
- Fetch paginated results from an API.
- Implement search, pagination, and IMDB links.
Topics Covered:
- API calls & pagination
- State management in React (useState, useEffect)
- Performance optimizations
Follow-ups:
- How would you handle large datasets efficiently?
- How would you improve the UX?
- How would you structure this for production?
Round 3: Technical 2 (Backend + API Design) (1 hour)
Problem: Find the fastest marathon runner
- API was paginated, so we needed an efficient way to fetch data.
- Consider rate limits & failure handling.
Topics Covered:
- Handling paginated API responses
- Optimizing for performance & rate limits
- Error handling & retries
Follow-ups:
- How would you optimize API calls for large data?
- How do you handle API failures in production?
- What if the API had strict rate limits?
Compensation Details - https://leetcode.com/discuss/post/6599578/godaddy-offer-sde2-pune-remote-by-priya_-m0to/
Interview Questions (3)
A discussion with the Hiring Manager about:
- Background & past experience
- Team culture & collaboration
- Challenges faced in previous roles
Problem: Build a Movie Search Page in React.
- Fetch paginated results from an API.
- Implement search, pagination, and IMDB links.
Topics Covered:
- API calls & pagination
- State management in React (useState, useEffect)
- Performance optimizations
Follow-ups:
- How would you handle large datasets efficiently?
- How would you improve the UX?
- How would you structure this for production?
Problem: Find the fastest marathon runner
- API was paginated, so we needed an efficient way to fetch data.
- Consider rate limits & failure handling.
Topics Covered:
- Handling paginated API responses
- Optimizing for performance & rate limits
- Error handling & retries
Follow-ups:
- How would you optimize API calls for large data?
- How do you handle API failures in production?
- What if the API had strict rate limits?