Scale Engineer

Senior SWE

Software EngineerSenior MTSHard

This interview process is designed to assess candidates for the Senior Software Engineer (Senior MTS) role at Salesforce. It evaluates technical proficiency, problem-solving skills, system design capabilities, and cultural fit within the Salesforce environment.

Rounds·4

Timeline·~15d

Experience·5 - 10 yrs

Comp band·US$140000 - US$180000

Interview time·180 min

Evaluation

What they measure.

  • Technical depth and breadth in relevant areas.
  • Problem-solving approach and analytical skills.
  • System design capabilities, including scalability, reliability, and maintainability.
  • Coding proficiency and best practices.
  • Communication skills and ability to articulate technical concepts.
  • Collaboration and teamwork.
  • Leadership potential and mentorship ability.
  • Cultural fit with Salesforce values (Trust, Customer Success, Innovation, Equality).

Preparation

How to prepare.

Tips

  1. Thoroughly review data structures and algorithms, focusing on time and space complexity.
  2. Practice coding problems on platforms like LeetCode, HackerRank, or AlgoExpert, targeting medium to hard difficulty.
  3. Study system design principles, common patterns (e.g., microservices, caching, load balancing), and scalability concepts.
  4. Prepare to discuss your past projects in detail, highlighting your contributions, technical challenges, and solutions.
  5. Understand Salesforce's core products and values. Research the specific team you are interviewing for.
  6. Practice behavioral questions using the STAR method (Situation, Task, Action, Result).
  7. Be prepared to discuss your experience with cloud platforms (AWS, Azure, GCP) and relevant technologies.
  8. Review fundamental computer science concepts like operating systems, databases, and networking.
  9. Engage in mock interviews to simulate the interview environment and receive feedback.

Study plan

Fig · Study plan — 04 phases

01 / 04
01

Phase 01 of 04

Data Structures and Algorithms

Weeks 1-2: DSA fundamentals and practice (2-3 problems/day).

Weeks 1-2: Focus on Data Structures and Algorithms. Cover arrays, linked lists, trees, graphs, hash tables, heaps, sorting, searching, dynamic programming, and greedy algorithms. Practice implementing these and analyzing their time/space complexity. Aim for 2-3 problems per day.

Questions

Commonly asked.

  • Design a distributed caching system.
  • How would you design a rate limiter for an API?
  • Explain the CAP theorem and its implications.
  • Describe a challenging bug you encountered and how you debugged it.
  • Tell me about a time you had to make a significant technical trade-off.
  • How do you approach code reviews?
  • What are your thoughts on microservices vs. monolith architecture?
  • Design a system to handle real-time analytics for a large user base.
  • How would you optimize a slow database query?
  • Describe your experience with CI/CD pipelines.
  • Tell me about a time you failed. What did you learn?
  • How do you stay updated with new technologies?

Locations

Regional differences.

Fig · Regions — 03 locations

01 / 03

Location

Seattle

Interview focus

Deep understanding of distributed systems and microservices architecture.Ability to design scalable, fault-tolerant, and performant systems.Proficiency in cloud technologies (AWS, Azure, GCP).Strong coding skills in at least one object-oriented language (Java, Python, C++).Experience with data structures and algorithms, particularly in optimizing for performance.Seattle: Cloud-native design patterns, containerization (Docker, Kubernetes).San Francisco: Potentially more focus on data engineering, real-time processing, or specific domain knowledge depending on the team.

Common questions

  • How would you design a real-time notification system for a large-scale application like Salesforce?
  • Describe a complex technical challenge you faced and how you overcame it, focusing on your decision-making process.
  • Discuss your experience with distributed systems and how you've handled issues like eventual consistency or fault tolerance.
  • In the Seattle office, there's a strong emphasis on cloud-native architectures. Be prepared to discuss your experience with AWS/Azure/GCP services and how they can be leveraged for scalability and reliability.
  • For the San Francisco office, expect more questions around high-frequency trading systems or large-scale data processing if the team has a focus in those areas. Understanding of low-latency systems might be beneficial.

Tips

  • For Seattle candidates: Familiarize yourself with AWS services like EC2, S3, Lambda, DynamoDB, and Kubernetes. Practice designing systems that leverage these services.
  • For San Francisco candidates: If applying to a data-intensive team, brush up on big data technologies like Spark, Hadoop, and Kafka. Understand data modeling and database design principles.
  • Both locations: Be ready to articulate your thought process clearly and concisely. Practice whiteboarding complex system designs.
  • Emphasize your contributions and leadership in past projects.
  • Be prepared to discuss trade-offs in your design decisions.

Rounds

Round-by-round.

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

DSA

Coding questions at Salesforce.

Frequently reported on Salesforce loops

View all at Salesforce

Other guides

More at Salesforce.