LinkedIn - Staff Software Engineer Interview

Overview

Interviewed with LinkedIn for a Staff Software Engineer position. The process consisted of 5 rigorous rounds over 3 days covering DSA, Concurrency, and High-Level Design.

Interview Format: Virtual (Video Call + CoderPad) Total Rounds: 5 Duration: 3 days

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Round 1: Screening Round

Duration: ~45 minutes

Topics Covered

• Level Order Traversal (tree problem)
• String Optimization (append operations)
• Operating Systems Concepts (threads/processes)
• Project Overview and Architecture Discussions

Key Learnings

• Strong OS fundamentals expected
• Be prepared to optimize string operations
• Have clear examples of impactful projects ready

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Round 2: DSA - Coding Module 1

Date: Tuesday, August 27, 2024 Duration: ~1.5 hours

Problem: Maximum Window Substring

Find the minimum window in string s that contains all characters in string t.

Approach: Sliding window with two pointers and frequency map

Complexity: O(n + m) time, O(m) space

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Round 3: DSA - Coding Module 2

Date: Tuesday, August 27, 2024 Duration: ~1.5 hours

Problem 1: Tree Boundary Nodes

Print left boundary nodes of a tree, delete them, and repeat recursively.

Problem 2: Collinear Points

Find the maximum number of points that lie on the same straight line in a 2D plane.

Key Concepts: Tree modification, geometry, slope calculations

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Round 4: Concurrency

Date: Wednesday, August 28, 2024 Duration: ~1.5 hours

Topics Covered

Conceptual Questions:

• Threads vs Processes
• Synchronization mechanisms (mutex, semaphore, monitors)
• Deadlock conditions and prevention
• Producer-Consumer problem
• Thread pooling

Coding Problem: Job Scheduler

Design and implement a thread-safe job scheduler with priorities, recurring jobs, and cancellation support.

Key Concepts: Concurrency primitives, thread safety, priority queues

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Round 5: High-Level Design

Date: Wednesday, August 28, 2024 Duration: ~1.5 hours

Problem: Metrics Aggregation System

Design a system to handle millions of events per second with real-time aggregations and queries.

Key Components:

• Ingestion Layer (Kafka)
• Processing Layer (Flink/Spark Streaming)
• Storage Layer (Time-series DB)
• Query Layer (Redis cache + query optimizer)

Scale: 1M metrics, 100TB storage, sub-second query latency

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Key Takeaways

Preparation Time: 3-4 months

Focus Areas:

• Strong DSA fundamentals (trees, graphs, sliding window)
• Deep concurrency understanding
• System design with distributed systems
• Real-world scaling experience

Tips:

• Practice CoderPad (code without IDE)
• Focus heavily on concurrency patterns
• Discuss trade-offs in system design
• Use real examples from experience
• Communicate thought process clearly