FactSet

Software Engineer

Software EngineerSenior Software EngineerMedium to Hard

FactSet is looking for a Senior Software Engineer to join our dynamic team. This role involves designing, developing, and maintaining high-quality software solutions that power our financial data and analytics platforms. You will collaborate with cross-functional teams to deliver innovative products and contribute to the technical growth of the engineering department.

Rounds

4

Timeline

~14 days

Experience

5 - 10 yrs

Salary Range

US$140000 - US$180000

Total Duration

180 min

Overall Evaluation Criteria

Technical Skills

Problem-solving skills
Algorithmic knowledge
Data structure proficiency
Code quality and efficiency
Ability to write clean, maintainable, and testable code

System Design & Architecture

System design capabilities
Scalability and performance considerations
Understanding of distributed systems
Architectural patterns and trade-offs
Experience with cloud technologies

Behavioral & Cultural Fit

Communication clarity
Teamwork and collaboration
Adaptability and learning agility
Ownership and accountability
Cultural fit with FactSet's values

Domain & Tooling Expertise

Experience with relevant programming languages (Java, Python, C++)
Familiarity with financial data and markets
Proficiency in database technologies
Experience with testing frameworks
Knowledge of CI/CD and DevOps practices

Preparation Tips

1Review fundamental data structures and algorithms.
2Practice coding problems on platforms like LeetCode, HackerRank, or AlgoExpert.
3Study system design principles and common architectural patterns.
4Prepare to discuss your past projects and technical contributions in detail.
5Research FactSet's company culture, values, and products.
6Understand the STAR method (Situation, Task, Action, Result) for behavioral questions.
7Practice mock interviews to simulate the actual interview experience.

Study Plan

1

Data Structures and Algorithms

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

Weeks 1-2: Focus on core data structures (Arrays, Linked Lists, Trees, Graphs, Hash Tables) and algorithms (Sorting, Searching, Dynamic Programming, Recursion). Practice implementing these from scratch and analyze their time and space complexity. Solve at least 2-3 problems per day.

2

System Design

Weeks 3-4: System Design principles. Study scalability, databases, and microservices.

Weeks 3-4: Dive into system design concepts. Study topics like scalability, availability, reliability, load balancing, caching, databases (SQL/NoSQL), message queues, and microservices. Work through common system design interview questions and practice drawing diagrams.

3

Behavioral Preparation

Week 5: Behavioral questions preparation using STAR method. Research FactSet.

Week 5: Prepare for behavioral questions. Reflect on your past experiences and prepare specific examples using the STAR method. Think about situations related to teamwork, problem-solving, leadership, and handling challenges. Also, research FactSet's values and mission.

4

Technology & Mock Interviews

Week 6: Technology review (Java/Python, Cloud), resume deep-dive, and mock interviews.

Week 6: Focus on specific technologies relevant to FactSet, such as Java/Python, cloud platforms (AWS/Azure/GCP), and financial data concepts. Review your resume and be ready to discuss any project or technology listed in detail. Conduct mock interviews.

Commonly Asked Questions

Tell me about a time you had to deal with a difficult stakeholder. How did you handle it?
Design a URL shortening service like bit.ly.
What are the differences between processes and threads?
How would you optimize a slow database query?
Describe a situation where you disagreed with your manager. What did you do?
Implement a function to find the k-th largest element in an unsorted array.
Explain the concept of eventual consistency.
How do you approach code reviews?
Tell me about a project you are particularly proud of.
Design a system to handle real-time notifications for a social media platform.

Location-Based Differences

New York

Interview Focus

System Design and ScalabilityProblem-solving and Algorithmic ThinkingExperience with distributed systemsProficiency in Java/Python/C++ and relevant frameworksUnderstanding of financial markets and data

Common Questions

How would you design a system to handle real-time stock price updates for millions of users?

Describe a complex technical challenge you faced and how you overcame it.

What are your thoughts on microservices vs. monolithic architecture for a financial data platform?

How do you ensure code quality and maintainability in a large codebase?

Discuss your experience with cloud platforms (AWS, Azure, GCP) and their services relevant to data processing and storage.

Tips

Be prepared to discuss your experience with large-scale systems and distributed computing.
Familiarize yourself with common financial data structures and APIs.
Practice explaining your thought process clearly and concisely.
Highlight any experience with performance optimization and low-latency systems.
Research FactSet's products and services to understand our business context.

London

Interview Focus

Data Structures and AlgorithmsSoftware Development Best PracticesDatabase Design and OptimizationConcurrency and ParallelismDebugging and Troubleshooting

Common Questions

How would you design a data pipeline for processing large volumes of historical financial data?

Explain the trade-offs between different database technologies (SQL vs. NoSQL) for storing financial time-series data.

Describe your approach to testing complex financial applications.

How do you handle concurrency and multithreading in your applications?

What are your strategies for debugging and troubleshooting production issues in a high-availability environment?

Tips

Brush up on your data structures and algorithms, especially those relevant to data manipulation and searching.
Be ready to write code on a whiteboard or shared editor.
Understand the principles of clean code and design patterns.
Prepare examples of how you've improved system performance or reliability.
Showcase your ability to work effectively in a team environment.

San Francisco

Interview Focus

API Design and DevelopmentDevOps and Cloud InfrastructureTechnical Leadership and MentorshipCommunication and CollaborationContinuous Learning

Common Questions

How do you approach designing APIs for financial data services?

Discuss your experience with containerization technologies like Docker and orchestration tools like Kubernetes.

What are your thoughts on CI/CD pipelines and their importance in software development?

How do you stay updated with the latest trends and technologies in software engineering?

Describe a situation where you had to influence technical decisions within a team.

Tips

Be prepared to discuss your experience with modern software development practices.
Highlight your contributions to team success and technical mentorship.
Demonstrate your understanding of cloud-native architectures.
Showcase your ability to communicate technical concepts to both technical and non-technical audiences.
Be ready to talk about your career aspirations and how they align with FactSet's goals.

Process Timeline

1
Technical Coding Round 145m
2
System Design Round60m
3
Behavioral / Manager Round45m
4
Final Round30m

Interview Rounds

4-step process with detailed breakdown for each round

1

Technical Coding Round 1

Coding challenge focused on data structures and algorithms.

Data Structures And AlgorithmsMedium
45 minSoftware Engineer / Senior Software Engineer

This round focuses on your core computer science fundamentals. You will be asked to solve one or two coding problems, typically involving data structures and algorithms. The interviewer will assess your ability to analyze the problem, devise an efficient solution, write clean and correct code, and discuss the time and space complexity of your approach. Be prepared to explain your thought process throughout the problem-solving exercise.

What Interviewers Look For

Strong understanding of fundamental data structures and algorithmsAbility to translate a problem into a working code solutionLogical thinking and systematic approach to problem-solvingAttention to detail

Evaluation Criteria

Correctness of the solution
Efficiency (Time and Space Complexity)
Code clarity and readability
Problem-solving approach
Handling of edge cases

Questions Asked

Given a binary tree, find its inorder traversal.

TreeRecursionIteration

Find the first non-repeating character in a string.

StringHash MapArray

Implement a function to reverse a linked list.

Linked ListPointers

Preparation Tips

1Practice coding problems on platforms like LeetCode, focusing on Medium difficulty.
2Review common data structures (arrays, linked lists, trees, graphs, hash maps) and algorithms (sorting, searching, dynamic programming).
3Practice explaining your solution out loud as you code.
4Be ready to discuss trade-offs of different approaches.

Common Reasons for Rejection

Inability to articulate thought process clearly
Incorrect or inefficient algorithmic solutions
Poor coding practices (e.g., lack of comments, poor variable naming)
Failure to consider edge cases and constraints
2

System Design Round

Design a scalable system based on a given problem statement.

System DesignHard
60 minSenior Software Engineer / Engineering Manager

This round assesses your ability to design large-scale systems. You'll be presented with an open-ended problem (e.g., design Twitter's feed, design a URL shortener) and expected to break it down, identify requirements, propose a high-level design, and then dive deeper into specific components. Focus on scalability, availability, data storage, APIs, and potential bottlenecks. Be prepared to justify your design choices and discuss trade-offs.

What Interviewers Look For

Ability to design complex, scalable, and reliable systemsUnderstanding of distributed systems conceptsExperience with various architectural patternsPragmatic approach to problem-solvingClear communication of technical ideas

Evaluation Criteria

Scalability of the proposed design
Robustness and fault tolerance
Clarity and completeness of the design
Understanding of trade-offs
Knowledge of relevant technologies (databases, caching, messaging)

Questions Asked

Design a system like TinyURL.

System DesignScalabilityDatabasesAPIs

Design a news feed system for a social media platform.

System DesignScalabilityDatabasesCachingAPIs

Design an API rate limiter.

System DesignDistributed SystemsAlgorithms

Preparation Tips

1Study common system design patterns and concepts (load balancing, caching, databases, message queues).
2Practice designing systems like Twitter, Facebook, Uber, etc.
3Understand the trade-offs between different technologies and architectural choices.
4Be prepared to draw diagrams and explain your design clearly.

Common Reasons for Rejection

Lack of clarity in system design approach
Failure to consider scalability and performance bottlenecks
Inability to justify design choices and trade-offs
Overlooking critical components or requirements
3

Behavioral / Manager Round

Behavioral questions to assess past experiences and cultural fit.

Behavioral InterviewMedium
45 minEngineering Manager / Director

This round focuses on your behavioral and situational responses. The interviewer will ask questions about your past experiences, how you handle specific work scenarios, your motivations, and your career goals. Use the STAR method (Situation, Task, Action, Result) to structure your answers. This is also an opportunity for you to ask questions about the team, role, and company culture.

What Interviewers Look For

Evidence of collaboration and teamworkAbility to handle challenging situations and learn from mistakesStrong communication skillsMotivation and passion for software engineeringAlignment with FactSet's culture

Evaluation Criteria

Teamwork and collaboration skills
Problem-solving approach in past experiences
Adaptability and learning agility
Communication effectiveness
Cultural fit and alignment with FactSet's values

Questions Asked

Tell me about a time you failed. What did you learn from it?

BehavioralLearningResilience

Describe a situation where you had to work with a difficult team member.

BehavioralTeamworkConflict Resolution

Why are you interested in FactSet?

BehavioralMotivationCompany Fit

Preparation Tips

1Prepare specific examples using the STAR method for common behavioral questions (teamwork, conflict resolution, challenges, successes).
2Reflect on your strengths and weaknesses.
3Think about why you want to work at FactSet and for this specific role.
4Prepare thoughtful questions to ask the interviewer.

Common Reasons for Rejection

Lack of alignment with company values
Poor communication or interpersonal skills
Inability to provide specific examples for behavioral questions
Lack of enthusiasm or interest in the role/company
4

Final Round

Final discussion with a senior leader to assess overall fit.

Final Round / Executive InterviewMedium to Hard
30 minSenior Engineering Leader / Hiring Manager

This is often a final round where a senior leader or hiring manager consolidates feedback from previous interviews. They may ask a few more targeted questions to clarify any doubts or probe deeper into specific areas. This is also a crucial opportunity for you to ask any remaining questions and ensure your understanding of the role and team.

What Interviewers Look For

Confirmation of skills and experience from previous roundsPotential for growth and leadershipOverall fit for the team and company

Evaluation Criteria

Overall technical competence
Consistency in performance
Alignment with the senior level expectations
Ability to contribute to team goals

Questions Asked

What are your career aspirations for the next 3-5 years?

BehavioralCareer Goals

How do you mentor junior engineers?

BehavioralLeadershipMentorship

Preparation Tips

1Review your performance in previous rounds.
2Be prepared to reiterate your interest and qualifications.
3Have thoughtful questions ready about the team's roadmap, challenges, and culture.

Common Reasons for Rejection

Inconsistent performance across rounds
Lack of depth in technical knowledge
Poor communication during technical discussions
Not meeting the bar for a Senior Software Engineer role

Commonly Asked DSA Questions

Frequently asked coding questions at FactSet

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