Full Stack Web Application Engineer
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Job Description & Responsibilities
About the Role
Zepto is actively hiring a high-impact Full Stack Web Application Engineer to join their engineering team. In this position, you will work on mission-critical features, high-throughput architectures, resilient APIs, and modern cloud infrastructure.
Key Responsibilities
- Design, build, and deploy reliable software services and distributed systems with minimal downtime.
- Collaborate across engineering, product management, and design to ship customer-facing improvements.
- Write robust, unit-tested, and maintainable code adhering to solid engineering principles.
- Participate in peer code reviews, architectural discussions, and observability/monitoring improvements.
Requirements & Preferred Qualifications
- Solid foundations in data structures, algorithms, object-oriented design, and distributed systems.
- Hands-on experience with modern backend, fullstack, or cloud stacks (Go, Node.js, Python, React, or Java).
- Working knowledge of databases (PostgreSQL, MySQL, MongoDB, or Redis) and performance optimization.
- Passion for problem-solving, clean code, and working in high-ownership engineering environments.
How to Apply
Applications are reviewed directly by the engineering and talent acquisition team at Zepto. Review full role specifics and submit your profile using the direct application portal below.
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Applications are reviewed directly by Zepto.
Crack the Technical Interview for Full Stack Web Application Engineer
Core Engineering Concepts Interviewers Will Test:
- Database Indexing & Query Plans: Explain B-Tree indexes, composite index ordering, and how unindexed foreign keys lead to full table scans.
- Cache Invalidation & Redis Patterns: Differentiate between Cache-Aside, Write-Through, and handle Cache Stampedes with distributed locks (Redlock).
- API Idempotency & Concurrency: How to implement idempotency keys for payment/checkout endpoints using unique database constraints and Redis TTL tokens.
- Rate Limiting Algorithms: Token Bucket vs Leaky Bucket vs Sliding Window Log implementation trade-offs at scale.