Scale Engineer

Software Engineer II

Software Engineer65Medium to Hard

This interview process is for a Software Engineer II (Level 65) position at Synopsys. It is designed to assess a candidate's technical proficiency, problem-solving skills, and cultural fit within the company.

Rounds·3

Timeline·~14d

Experience·4 - 7 yrs

Comp band·US$120000 - US$150000

Interview time·150 min

Evaluation

What they measure.

  • Problem-solving ability
  • Algorithmic thinking
  • Data structures knowledge
  • Coding proficiency
  • System design and architecture
  • Scalability and performance considerations
  • Communication skills
  • Teamwork and collaboration
  • Adaptability and learning agility
  • Behavioral fit with Synopsys culture

Preparation

How to prepare.

Tips

  1. Review fundamental data structures (arrays, linked lists, trees, graphs, hash tables) and algorithms (sorting, searching, dynamic programming, graph traversal).
  2. Practice coding problems on platforms like LeetCode, HackerRank, or AlgoExpert, focusing on medium to hard difficulty.
  3. Study system design concepts, including scalability, reliability, availability, databases, caching, load balancing, and message queues.
  4. Understand common design patterns and architectural styles (e.g., microservices, RESTful APIs).
  5. Prepare for behavioral questions by reflecting on your past experiences using the STAR method (Situation, Task, Action, Result).
  6. Research Synopsys's products, values, and recent news to tailor your answers and show genuine interest.
  7. Practice explaining your thought process clearly and concisely, both verbally and through whiteboarding/coding.

Study plan

Fig · Study plan — 05 phases

01 / 05
01

Phase 01 of 05

Data Structures and Algorithms

Weeks 1-2: Data Structures & Algorithms fundamentals. Practice 2-3 problems/day.

Weeks 1-2: Focus on core data structures and algorithms. Cover arrays, linked lists, stacks, queues, trees (binary trees, BSTs, AVL trees), heaps, hash tables, and graphs. Practice sorting algorithms (quicksort, mergesort), searching algorithms (binary search), and basic dynamic programming problems. Aim to solve 2-3 problems per day.

Questions

Commonly asked.

  • Given an array of integers, find the contiguous subarray with the largest sum.
  • Design a URL shortening service like bit.ly.
  • Implement a function to reverse a linked list.
  • How would you design a system to handle real-time notifications for a social media platform?
  • Explain the difference between processes and threads.
  • Describe a time you had to deal with ambiguity in a project.
  • What are the advantages of using a NoSQL database over a relational database for certain use cases?
  • Write a function to find the k-th smallest element in an unsorted array.
  • How do you approach testing your code?
  • Tell me about a time you received constructive criticism and how you acted on it.

Locations

Regional differences.

Fig · Regions — 02 locations

01 / 02

Location

Bangalore, India

Interview focus

Emphasis on practical application of data structures and algorithms.Deep dive into system design principles relevant to large-scale applications.Behavioral questions focusing on collaboration and problem-solving in a team environment.

Common questions

  • Discuss a challenging technical problem you solved in a previous role.
  • How do you approach debugging complex issues?
  • Describe a time you had to work with a difficult stakeholder.
  • What are your thoughts on microservices vs. monolithic architectures?
  • Explain the concept of eventual consistency.

Tips

  • Be prepared to whiteboard solutions for algorithmic problems.
  • Familiarize yourself with common design patterns and architectural styles.
  • Have specific examples ready to illustrate your experience with teamwork and conflict resolution.

Rounds

Round-by-round.

Expand a step for evaluation criteria, sample questions, and prep notes.

DSA

Coding questions at Synopsys.

Frequently reported on Synopsys loops

View all at Synopsys

Other guides

More at Synopsys.