A Software Engineer at Pubmatic works at the intersection of extreme scale, high throughput, and ultra-low latency. As a leading player in the programmatic advertising industry, Pubmatic processes trillions of ad impressions daily, requiring an engineering infrastructure that can make real-time bidding decisions in milliseconds. In this role, you will be responsible for designing, building, and optimizing software that manages massive data pipelines, complex ad-serving algorithms, and highly distributed systems.

The impact of your work as a Software Engineer is immediate and highly visible. You will contribute to core products like high-volume ad servers, real-time analytics dashboards, and robust data ingestion systems. Engineering teams at Pubmatic tackle complex challenges in distributed computing, storage optimization, and concurrency, making this an exceptionally rewarding environment for developers who thrive on solving hard technical problems.

To succeed in this position, you must possess a deep understanding of core computer science principles, data structures, and algorithms. Whether you are optimizing a database query, designing a fault-tolerant microservice, or implementing a threading model to handle concurrent requests, your engineering decisions will directly influence the platform's efficiency and reliability.

The following questions are compiled from real interview experiences at Pubmatic. While the exact questions you receive will depend on your target team and seniority, preparing for these common patterns will help you build a solid foundation for your technical discussions.

Data Structures & Algorithms

This category tests your ability to write clean, efficient code and analyze time and space complexity under pressure.

• Write an algorithm to reverse the string "I love My India" to "India My love I" without using any built-in split functions.
• Given an array of integers representing daily stock market data, find the specific days to buy and sell to maximize profit.

Succeeding in the Pubmatic interview process requires a balanced preparation strategy that covers both theoretical computer science and practical system design.

Algorithmic Problem Solving – You must be highly proficient in fundamental data structures such as arrays, linked lists, trees, and hash maps. Interviewers look for clean, readable code and expect you to explain the time and space complexity of your solutions. Practice implementing algorithms on a whiteboard or virtual notepad without relying on IDE autocompletion.

System Design & Scalability – Given the ad-tech domain, you need to demonstrate that you can think about systems at scale. Focus on understanding distributed caching, database sharding, load balancing, and message queues. For low-level design, practice translating requirements into clear object-oriented designs with well-defined interfaces.

Language & Platform Depth – Whether your expertise lies in Java, C++, Go, or JavaScript, expect deep-dive questions into runtime behavior, memory management, and concurrency. You should be prepared to discuss language-specific features, framework architectures (like Spring or Angular), and performance profiling techniques.

Collaboration & Communication – Throughout the technical rounds, your communication skills are under evaluation. Explain your thought process clearly, state your assumptions, and remain receptive to feedback. When interviewers challenge your approach, treat it as a collaborative debugging session rather than a test of egos.

The interview process for a Software Engineer at Pubmatic is comprehensive and designed to test your technical limits across multiple domains. Typically spanning two to three weeks, the process evaluates core coding skills, system design capabilities, and cultural alignment.

The journey begins with an initial screening phase, which often includes a technical assessment. Following this, you will proceed through multiple rounds of technical interviews, culminating in a managerial and HR discussion. The rounds are structured to gradually increase in complexity, allowing the engineering team to understand both your foundational knowledge and your architectural capabilities.

The timeline above outlines the standard progression of the hiring pipeline. Candidates should use this timeline to pace their preparation, ensuring they dedicate sufficient time to core CS fundamentals before moving on to complex system design scenarios. While the exact number of rounds can vary depending on the seniority of the role, the emphasis on rigorous technical evaluation remains consistent.

To excel in the Pubmatic technical interviews, you must understand exactly what the engineering panel is looking for in each key evaluation area.

Data Structures & Algorithms

This area is the foundation of the technical evaluation. The team wants to see if you can write optimal code to solve complex problems under time constraints.

Be ready to go over:

• Array and String Manipulation – Techniques like two-pointer approaches, sliding windows, and in-place transformations.
• Linked Lists and Trees – Traversal algorithms, cycle detection, and binary tree manipulations (such as finding tree depth or views).
• Searching and Sorting – Binary search applications and custom sorting logic.
• Advanced concepts (less common) – Dynamic programming, trie implementations, and graph traversals (DFS/BFS).

Example scenarios:

• "Implement an efficient algorithm to rotate an array of size N by K steps."
• "Write a function to check if a given binary tree is a valid binary search tree."
• "Determine if two strings are K-Anagrams of each other."

System Design (LLD & HLD)

System design rounds assess your ability to build robust architectures that handle massive scale. You will face both High-Level Design (HLD) and Low-Level Design (LLD) challenges.

Be ready to go over:

• Database Schema & Indexing – Designing schemas for high-write workloads and optimizing query performance using indexes.
• Concurrency & Caching – Implementing thread-safe cache mechanisms and managing race conditions.
• Scalability Patterns – Load balancing, horizontal partitioning, and asynchronous processing using message brokers.
• Advanced concepts (less common) – Designing real-time data streaming pipelines and microservices orchestration.

Example scenarios:

• "Design a high-throughput, fault-tolerant logging and archival system."
• "Create a low-level object-oriented design for a multi-player Tic-Tac-Toe game."
• "Explain how you would design and scale a rate-limiting service for an API gateway."

Language & Core CS Fundamentals

This section evaluates your practical development skills and your understanding of how software interacts with hardware.

Be ready to go over:

• Concurrency & Multithreading – Thread lifecycles, synchronization blocks, and concurrent collections.
• Operating System Concepts – Process vs. thread, memory management, and Unix systems administration.
• Object-Oriented Programming (OOP) – Design patterns, inheritance, polymorphism, and encapsulation.
• Advanced concepts (less common) – Garbage collection tuning, memory leak detection, and network protocols.

Example scenarios:

• "How would you troubleshoot a thread deadlock in a production environment?"
• "Explain how the operating system handles virtual memory and page faults."