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LinkedIn Coding Interview Questions

Tackle coding problems modeled after the systems, scale, and speed that power LinkedIn, the world's largest professional network.
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LinkedIn’s engineering interviews reward more than just correct answers—they test how you write scalable code, break down complex systems, and communicate clearly under time pressure. These questions are built to mirror real interview themes at LinkedIn, from traversing massive connection graphs to processing millions of data events with low latency. You’ll solve coding problems grounded in practical use cases: designing features around LinkedIn’s graph, optimizing performance for large-scale data operations, and maintaining clarity in logic even under constraints. This isn’t just a prep set; it’s a simulation of how LinkedIn thinks about engineering at scale. Every question gives you the chance to practice coding while explaining trade-offs, edge cases, and design decisions, just like you would in a real LinkedIn technical screen.
LinkedIn’s engineering interviews reward more than just correct answers—they test how you write scalable code, break down comple...Show More

WHAT YOU'LL LEARN

Designing algorithms to navigate connection graphs, messaging paths, and feed updates.
Writing performant, readable code that reflects real system constraints.
Debugging logic for large-scale input sets and user-driven interaction flows.
Balancing clarity and efficiency while solving under time pressure.
Communicating design reasoning and technical decisions in the way LinkedIn engineers are expected to.
Designing algorithms to navigate connection graphs, messaging paths, and feed updates.

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Developed by MAANG Engineers
Every Educative lesson is designed by a team of ex-MAANG software engineers and PhD computer science educators, and developed in consultation with developers and data scientists working at Meta, Google, and more. Our mission is to get you hands-on with the necessary skills to stay ahead in a constantly changing industry. No video, no fluff. Just interactive, project-based learning with personalized feedback that adapts to your goals and experience.

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