Factset Software Engineer Interview Guide

The 60-second brief

As a Software Engineer at Factset, you play a crucial role in developing and maintaining the sophisticated software solutions that drive our financial data services. Your work directly impacts our clients, providing them with the tools necessary to analyze complex financial information efficiently. In an environment that values innovation, you will be at the forefront of enhancing existing products and crafting new features that address the evolving needs of our users. This position is central to the success of Factset’s wide array of products, ranging from data analytics platforms to real-time financial data feeds. You will collaborate with cross-functional teams, including product managers and data scientists, to design robust systems that integrate seamlessly with our clients' workflows.

This guide is scoped to a Software Engineer candidate at Factset.

Focus areas

• Data Structures (DS)
• Algorithms & Problem Solving
• Coding Interviews

The Factset interview process

Factset candidates report 3 rounds over 3-5 weeks. The stages below are what candidates describe, not a published process.

Online Assessment

Initial assessment that evaluates your coding skills.

What to demonstrate

• Initial assessment that evaluates your coding skills
• Depth in Data Structures (DS)

How to prepare

• Answer aloud and timed: Explain the difference between a stack and a queue. Give examples of when you would use each.
• Answer aloud and timed: What is the time complexity of your solution for finding the longest substring without repeating characters?

Technical Interviews

Involves live coding exercises and discussions about your previous projects.

What to demonstrate

• Involves live coding exercises and discussions about your previous projects
• Depth in Data Structures (DS)

How to prepare

• Answer aloud and timed: Can you discuss the principles of object-oriented programming and how they apply to your recent projects?
• Answer aloud and timed: Describe a project where you used data structures effectively. What was the outcome?

Behavioral Questions

Mix of behavioral and technical questions to assess skills and team fit.

What to demonstrate

• Mix of behavioral and technical questions to assess skills and team fit
• Depth in Data Structures (DS)

How to prepare

• Prepare three examples from your own work, each with a decision you made and an outcome you can quantify.
• Re-read the description of the behavioral questions above and write down what you would ask to confirm before it.

Where candidates lose points

Practice Coding

Regularly solve coding challenges on platforms like LeetCode or HackerRank to sharpen your skills.

Understand Financial Concepts

Familiarize yourself with basic financial principles, as they may relate to the projects you’ll work on.

Prepare Behavioral Examples

Reflect on past experiences that demonstrate your teamwork, problem-solving skills, and adaptability.

Ask Questions

Prepare thoughtful questions to ask your interviewers about the company culture, team dynamics, and project challenges.

Questions & practice

What is the time complexity of your solution for finding the longest substring without repeating characters?

Medium · Technical / Domain Questions

Approach

1. Restate the input: its shape, its size, and what is guaranteed about it.
2. Name the brute-force solution and its complexity before improving on it.
3. Choose the data structure from the access pattern, not from familiarity.
4. State the target complexity and say which constraint rules the naive version out.

Follow-up

• How does this change if the input no longer fits in memory?
• What is the worst case, and how likely is it on real data?

Write a function to merge two sorted arrays into a single sorted array.

Medium · Coding / Algorithms

Approach

1. Restate the input: its shape, its size, and what is guaranteed about it.
2. Name the brute-force solution and its complexity before improving on it.
3. Choose the data structure from the access pattern, not from familiarity.
4. State the target complexity and say which constraint rules the naive version out.

Follow-up

• How does this change if the input no longer fits in memory?
• What is the worst case, and how likely is it on real data?

Given a binary tree, implement a function to perform a level-order traversal.

Medium · Coding / Algorithms

Approach

1. Restate the input: its shape, its size, and what is guaranteed about it.
2. Name the brute-force solution and its complexity before improving on it.
3. Choose the data structure from the access pattern, not from familiarity.
4. State the target complexity and say which constraint rules the naive version out.

Follow-up

• How does this change if the input no longer fits in memory?
• What is the worst case, and how likely is it on real data?

How would you implement a function to check if a string is a palindrome?

Medium · Coding / Algorithms

Approach

1. Restate the input: its shape, its size, and what is guaranteed about it.
2. Name the brute-force solution and its complexity before improving on it.
3. Choose the data structure from the access pattern, not from familiarity.
4. State the target complexity and say which constraint rules the naive version out.

Follow-up

• How does this change if the input no longer fits in memory?
• What is the worst case, and how likely is it on real data?

Describe your approach to optimizing a slow SQL query. What tools would you use?

Medium · Problem-Solving / Case Studies

Approach

1. Name the grain you start from and join outward from it.
2. Check whether any join is one-to-many before aggregating, or the sums inflate.
3. Say which index the query would use, and what makes it unusable.
4. Handle the rows that do not match: that is usually the actual question.

Follow-up

• How does the query change if that join becomes one-to-many?
• What happens to this when the table is ten times larger?

Find version gaps and relay lag with window functions

Medium · window functions · event tables · frame semantics

outbox_event holds event_id, aggregate_type, aggregate_id, aggregate_version, event_type, payload, status ('pending','published','dead'), attempts, created_at, published_at. A projection is missing rows and you must decide whether the relay skipped events or the consumer dropped them. Write three queries over the last seven days: one listing every aggregate_id whose published aggregate_version sequence has a hole, one giving per-day counts with a running total, and one returning the newest published event per aggregate. For each, say where the window function is evaluated relative to WHERE and LIMIT. PostgreSQL 16.

Approach

1. Gaps: compute lead(aggregate_version) OVER (PARTITION BY aggregate_id ORDER BY aggregate_version) in a subquery, then filter next_version <> aggregate_version + 1 in the outer query. Window functions are evaluated after WHERE, GROUP BY and HAVING and before the outer ORDER BY and LIMIT, so the predicate cannot sit in the same WHERE clause and PostgreSQL 16 has no QUALIFY.
2. Say what the seven-day filter does to the answer: it truncates every partition, so the first row per aggregate has no predecessor inside the window and a hole spanning the boundary is invisible. Widen the window, or join to resource.version as the authority for the true maximum.
3. Running total: SELECT date_trunc('day', created_at) AS d, count() AS n, sum(count()) OVER (ORDER BY date_trunc('day', created_at) ROWS UNBOUNDED PRECEDING). An aggregate inside a window call is legal because grouping runs before windowing. The grouping key is unique per row here so ROWS and RANGE agree, but write the frame anyway — over ungrouped rows with tied timestamps the default RANGE frame pulls in every peer row and the total jumps.
4. Newest per aggregate: DISTINCT ON (aggregate_id) ... ORDER BY aggregate_id, aggregate_version DESC is the cheap PostgreSQL-only form when an index matches that order; row_number() OVER (PARTITION BY aggregate_id ORDER BY aggregate_version DESC) = 1 is the portable form and needs a subquery for the same evaluation-order reason as the gap query.

Follow-up

• Relay failover redelivers events. Does a duplicate break the gap query, and how would you detect one from this table alone?
• Turn the gap check into a continuous monitor rather than a query someone runs after an incident. What does it watch?

Explain the difference between a stack and a queue. Give examples of when you would use each.

Medium · Technical / Domain Questions

Approach

1. Clarify what is being asked and what a complete answer contains.
2. State your assumptions explicitly before working the problem.
3. Say what you would check first and why it is the highest-information step.
4. Work from the requirement backwards to the design.

Follow-up

• What assumption would you test first?
• How would you know your answer was wrong?

Can you discuss the principles of object-oriented programming and how they apply to your recent projects?

Medium · Technical / Domain Questions

Approach

1. Clarify what is being asked and what a complete answer contains.
2. State your assumptions explicitly before working the problem.
3. Say what you would check first and why it is the highest-information step.
4. Work from the requirement backwards to the design.

Follow-up

• What assumption would you test first?
• How would you know your answer was wrong?

Describe a project where you used data structures effectively. What was the outcome?

Medium · Technical / Domain Questions

Approach

1. Clarify what is being asked and what a complete answer contains.
2. State your assumptions explicitly before working the problem.
3. Say what you would check first and why it is the highest-information step.
4. Work from the requirement backwards to the design.

Follow-up

• What assumption would you test first?
• How would you know your answer was wrong?

How would you design a system to manage user authentication for a web application?

Medium · Problem-Solving / Case Studies

Approach

1. Fix the scope first: who calls this, how often, and what they do when it fails.
2. Name the read and write paths separately; they rarely have the same bottleneck.
3. Choose a partition key and say what query it makes expensive.
4. State the consistency you need, and where you are willing to be stale.

Follow-up

• What breaks first when traffic grows ten times?
• How does this behave when that dependency is down for an hour?

If a user reports that the application is running slowly, how would you approach diagnosing the issue?

Medium · Problem-Solving / Case Studies

Approach

1. Clarify what is being asked and what a complete answer contains.
2. State your assumptions explicitly before working the problem.
3. Say what you would check first and why it is the highest-information step.
4. Work from the requirement backwards to the design.

Follow-up

• What assumption would you test first?
• How would you know your answer was wrong?

Exports duplicate a row range about once a week

Hard · leases · clock skew · idempotency

Roughly once a week an export writes a file containing a duplicated range of rows. The affected job_run rows show attempt = 1, status = succeeded, one started_at, and a lease_owner naming a different host from the one whose logs show the job starting. Leases last 30 seconds and are heartbeated every 10 from inside the handler; lease_expires_at is computed on the worker and compared against the database's now(). Find the mechanism, and give a fix that holds even if you cannot fix the clocks.

Approach

1. Start from the fact that eliminates the obvious answer. attempt = 1 means no retry was recorded, so this is not a re-run after failure; two workers ran the same row concurrently and the takeover path never touched the counter. lease_owner naming a host other than the one that started the job is the same statement from the other side.
2. Enumerate the mechanisms that cause a premature takeover, then find the signal that separates them. Either the lease genuinely expired because the heartbeat did not fire, which is what happens when the heartbeat runs on the handler's own thread and the handler makes a long blocking call, or it only appeared expired because two clocks disagree, since lease_expires_at is written from the worker's clock and evaluated against the database's. The discriminator is the distribution: incidents clustered on the longest exports indict the heartbeat, incidents clustered on one host indict skew. Measure both, and measure each host's offset against the database directly.
3. Read the reclaim query precisely. In PostgreSQL now() is transaction start time, not statement time, so a reclaimer holding a long transaction compares against an older timestamp than expected; clock_timestamp() is the statement-time function. This is worth ruling in or out before you redesign anything, because it changes which rows look expired.
4. Remove the second clock rather than trying to synchronise it. Issue and extend the lease in the database, with lease_expires_at = now() + interval '30 seconds' in both the claim and the heartbeat, so exactly one clock is ever compared and worker skew stops mattering to this predicate.

Follow-up

• The displaced worker has already streamed half the file to object storage. What makes that side effect safe to repeat?
• You now count takeovers. What alert fires on that counter, and at what threshold?

Suggested practice checklist

Built from the rounds and topics Factset candidates report.

Day 1 — Map the Factset loop

• Write out the reported sequence: Online Assessment, Technical Interviews, Behavioral Questions.
• For each round, write one sentence on what it is judging, from the description above, and mark the one you are least ready for.

Deliverable: A one-page map of the 3 reported rounds, with the weakest marked.

Day 2 — Work Data Structures (DS)

• Spend the session on Data Structures (DS), which Factset candidates report being tested on.
• Write one worked example in Data Structures (DS) and time yourself on it.

Deliverable: One timed worked example in Data Structures (DS).

Day 3 — Work Algorithms & Problem Solving

• Spend the session on Algorithms & Problem Solving, which Factset candidates report being tested on.
• Write one worked example in Algorithms & Problem Solving and time yourself on it.

Deliverable: One timed worked example in Algorithms & Problem Solving.

Day 4 — Work Coding Interviews

• Spend the session on Coding Interviews, which Factset candidates report being tested on.
• Write one worked example in Coding Interviews and time yourself on it.

Deliverable: One timed worked example in Coding Interviews.

Day 5 — Answer out loud: Technical / Domain Questions

• Answer aloud, timed: Explain the difference between a stack and a queue. Give examples of when you would use each.
• Answer aloud, timed: What is the time complexity of your solution for finding the longest substring without repeating characters?

Deliverable: Spoken answers to 2 reported Technical / Domain Questions question(s), under time.

Day 6 — Answer out loud: Problem-Solving / Case Studies

• Answer aloud, timed: How would you design a system to manage user authentication for a web application?
• Answer aloud, timed: If a user reports that the application is running slowly, how would you approach diagnosing the issue?

Deliverable: Spoken answers to 2 reported Problem-Solving / Case Studies question(s), under time.

Day 7 — Answer out loud: Coding / Algorithms

• Answer aloud, timed: Write a function to merge two sorted arrays into a single sorted array.
• Answer aloud, timed: Given a binary tree, implement a function to perform a level-order traversal.

Deliverable: Spoken answers to 2 reported Coding / Algorithms question(s), under time.

Behavioural preparation

Behavioural rounds judge the decision you made and what it cost.

Describe a challenging situation you faced in a team project. How did you resolve it?

Medium · Behavioral / Leadership

Approach

1. Pick a story where you made the decision, not one where you watched it.
2. State the situation in two sentences and spend the rest on the reasoning.
3. Give the blast radius: what could have broken, and what you measured.
4. Name the disagreement and how you resolved it with evidence.

Follow-up

• What would you do differently if you ran that again?
• How did you know your change caused the improvement?

How do you prioritize tasks when working on multiple projects?

Medium · Behavioral / Leadership

Approach

1. Pick a story where you made the decision, not one where you watched it.
2. State the situation in two sentences and spend the rest on the reasoning.
3. Give the blast radius: what could have broken, and what you measured.
4. Name the disagreement and how you resolved it with evidence.

Follow-up

• What would you do differently if you ran that again?
• How did you know your change caused the improvement?

What motivates you to work in the financial technology sector?

Medium · Behavioral / Leadership

Approach

1. Pick a story where you made the decision, not one where you watched it.
2. State the situation in two sentences and spend the rest on the reasoning.
3. Give the blast radius: what could have broken, and what you measured.
4. Name the disagreement and how you resolved it with evidence.

Follow-up

• What would you do differently if you ran that again?
• How did you know your change caused the improvement?