Scale Engineer

Software Engineer

Software EngineerDistinguished EngineerVery High

The Distinguished Engineer interview at FactSet is a rigorous process designed to assess deep technical expertise, strategic thinking, leadership potential, and the ability to drive innovation. Candidates are expected to demonstrate a mastery of software engineering principles, a proven track record of delivering complex, high-impact projects, and the capacity to mentor and influence other engineers. This role requires a strong understanding of system design, scalability, performance optimization, and a broad knowledge of various technologies and architectural patterns. The interview process is comprehensive, covering technical depth, problem-solving skills, behavioral aspects, and alignment with FactSet's culture and values.

Rounds·4

Timeline·~21d

Experience·12 - 20 yrs

Comp band·US$180000 - US$250000

Interview time·210 min

Evaluation

What they measure.

  • Depth and breadth of technical knowledge.
  • Problem-solving and analytical skills.
  • System design and architectural capabilities.
  • Leadership and mentorship potential.
  • Communication and interpersonal skills.
  • Strategic thinking and business acumen.
  • Cultural fit and alignment with FactSet values.

Preparation

How to prepare.

Tips

  1. Thoroughly review your resume and be prepared to discuss every project and accomplishment in detail.
  2. Deepen your understanding of core computer science concepts, including data structures, algorithms, operating systems, and databases.
  3. Study system design principles, focusing on scalability, reliability, availability, and performance.
  4. Familiarize yourself with FactSet's products, services, and the financial industry.
  5. Practice behavioral questions using the STAR method (Situation, Task, Action, Result).
  6. Prepare thoughtful questions to ask the interviewers about the role, team, and company.
  7. Review common interview questions for Distinguished Engineers and practice articulating your thought process.
  8. Understand FactSet's company culture, values, and mission.

Study plan

Fig · Study plan — 04 phases

01 / 04
01

Phase 01 of 04

Foundational Knowledge

Weeks 1-2: Core CS Fundamentals (Data Structures, Algorithms, OS, Databases). Practice coding problems.

Weeks 1-2: Focus on core computer science fundamentals. Review data structures (arrays, linked lists, trees, graphs, hash tables), algorithms (sorting, searching, dynamic programming, graph traversal), operating systems concepts (processes, threads, memory management), and database principles (SQL, NoSQL, indexing, transactions). Practice coding problems on platforms like LeetCode, HackerRank, focusing on medium to hard difficulty.

Questions

Commonly asked.

  • Describe a time you had to make a significant technical decision with incomplete information. How did you approach it, and what was the outcome?
  • Discuss a complex system you designed or significantly contributed to. What were the key challenges, and how did you address them?
  • How do you stay current with emerging technologies and industry trends? How have you incorporated new technologies into your work?
  • Tell me about a time you mentored a junior engineer or led a technical team. What was your approach to fostering growth and ensuring project success?
  • What are your thoughts on the future of financial technology, and how can FactSet best position itself for success in that landscape?
  • Describe a situation where you had to influence stakeholders with differing technical opinions. How did you reach a consensus?
  • How do you approach designing for high availability and disaster recovery in a distributed system?
  • Tell me about a time you identified and resolved a critical performance bottleneck in a large-scale application.
  • What are your strategies for managing technical debt and ensuring code quality in a fast-paced environment?
  • How do you see AI and machine learning impacting the financial services industry, and where do you see FactSet playing a role?
  • Walk me through a challenging project where you had to balance competing priorities (e.g., speed, cost, quality).
  • How do you approach designing APIs for internal and external consumption, ensuring robustness and ease of use?
  • Describe your experience with data modeling and database performance optimization for large datasets.
  • Tell me about a time you had to advocate for a new technology or architectural approach. What was the process, and what was the outcome?
  • What are the key considerations when designing for security and compliance in financial applications?

Locations

Regional differences.

Fig · Regions — 03 locations

01 / 03

Location

New York

Interview focus

Deep dive into architectural decisions and trade-offs.Strategic thinking and long-term vision for technology.Leadership and influence within a technical organization.Understanding of business impact and client needs.Adaptability to evolving market demands.

Common questions

  • Discuss a time you had to make a significant technical decision with incomplete information. How did you approach it, and what was the outcome?
  • Describe a complex system you designed or significantly contributed to. What were the key challenges, and how did you address them?
  • How do you stay current with emerging technologies and industry trends? How have you incorporated new technologies into your work?
  • Tell me about a time you mentored a junior engineer or led a technical team. What was your approach to fostering growth and ensuring project success?
  • What are your thoughts on the future of financial technology, and how can FactSet best position itself for success in that landscape?

Tips

  • Be prepared to discuss your most impactful projects in detail, focusing on your specific contributions and the business outcomes.
  • Articulate your thought process clearly, especially when discussing complex technical challenges and solutions.
  • Demonstrate a strong understanding of FactSet's business and how technology drives value for our clients.
  • Showcase your ability to think strategically and provide insights into future technology trends.
  • Highlight your experience in mentoring, leadership, and influencing technical direction.

Rounds

Round-by-round.

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

High

Data Structures And Algorithms · 60 min · Senior Software Engineer or Staff Engineer

This round focuses on assessing your fundamental computer science knowledge and your ability to translate problem statements into efficient code. You will be presented with one or two complex coding problems, typically involving data structures and algorithms. The interviewer will evaluate your approach to problem-solving, your coding style, your ability to optimize solutions, and your understanding of time and space complexity. Expect to write code on a whiteboard or in a shared editor, and be prepared to discuss your solution thoroughly.

What they look for

Clean, efficient, and correct code.Clear explanation of approach.Consideration of time and space complexity.Ability to handle follow-up questions and edge cases.Understanding of fundamental CS concepts.

Evaluation

  • Problem-solving ability.
  • Data structure and algorithm knowledge.
  • Coding proficiency.
  • Logical thinking.
  • Ability to explain thought process.

Sample questions

  • Given a binary tree, invert the tree.

    Data StructuresRecursionTree

  • Find the kth largest element in an unsorted array.

    AlgorithmsSortingQuickselect

  • Implement a function to determine if a string is a valid palindrome, considering only alphanumeric characters and ignoring cases.

    StringsTwo PointersAlgorithm

  • Given an array of integers, return indices of the two numbers such that they add up to a specific target.

    Hash TableTwo SumAlgorithm

Prep for this round

  1. 01Practice coding problems on platforms like LeetCode, HackerRank, focusing on medium to hard difficulty.
  2. 02Review common data structures (arrays, linked lists, trees, graphs, hash maps) and algorithms (sorting, searching, dynamic programming, graph traversal).
  3. 03Understand Big O notation for time and space complexity.
  4. 04Practice explaining your thought process out loud as you solve problems.
  5. 05Be prepared to discuss trade-offs between different approaches.

Common rejection reasons

  • ×Inability to articulate technical concepts clearly.
  • ×Lack of depth in core technical areas.
  • ×Poor problem-solving approach.
  • ×Failure to consider edge cases or scalability.
  • ×Weak communication skills.

DSA

Coding questions at FactSet.

Frequently reported on FactSet loops

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