Smartsheet Software Engineer Interview Guide

The 60-second brief

As a Software Engineer at Smartsheet, you will design, build, and scale systems that power modern enterprise work management. Millions of users across global organizations depend on Smartsheet to orchestrate workflows, manage complex projects, and automate critical business logic. In this role, your code directly impacts the platform's reliability, latency, and capability, supporting everything from dynamic collaborative sheets and interactive dashboards to enterprise-grade cloud integrations. The engineering organization at Smartsheet is navigating an exciting evolution, uniting human collaborative workflows with cloud-native automation and intelligent AI agents. Whether you join core platform teams such as App Core, backend automation units, or corporate systems engineering, you will encounter high-scale distributed systems challenges.

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

Focus areas

• System Design
• Data Structures & Algorithms (DSA)
• High-Traffic Scalability

The Smartsheet interview process

Smartsheet candidates report 4 rounds over 3-5 weeks. The stages below are what candidates describe, not a published process.

Recruiter Call

Initial call with a recruiter to discuss the candidate's background and role fit.

What to demonstrate

• Initial call with a recruiter to discuss the candidate's background and role fit
• Depth in System Design

How to prepare

• Be able to walk your CV end to end in two minutes, and say why this company specifically.
• Have your salary expectations, notice period and location constraints ready, and ask for the rest of the loop in writing.

Technical Assessment

Online technical assessment or preliminary technical screen with an engineer.

What to demonstrate

• Online technical assessment or preliminary technical screen with an engineer
• Depth in System Design

How to prepare

• Answer aloud and timed: Write an implementation of the atoi function (converting a string to a 32-bit signed integer) with complete edge-case handling.
• Answer aloud and timed: Given an array of strings, write a program to count unique words efficiently while discussing time and space complexity.

Technical Screen

Live coding session on platforms like CoderPad, combined with questions about data structures and system architecture.

What to demonstrate

• Live coding session on platforms like CoderPad, combined with questions about data structures and system architecture
• Depth in System Design

How to prepare

• Answer aloud and timed: Identify and implement a Binary Search Tree (BST) optimization for a given data lookup problem.
• Answer aloud and timed: Design an automated cloud outage detector and alert system similar to AWS Health.

Onsite Interview

Final loop consisting of 3 to 5 rounds covering coding, system design, object-oriented design, and behavioral evaluations.

What to demonstrate

• Final loop consisting of 3 to 5 rounds covering coding, system design, object-oriented design, and behavioral evaluations
• Depth in System Design

How to prepare

• Answer aloud and timed: Architectural design for a high-traffic RESTful API service supporting real-time collaborative document updates.
• Answer aloud and timed: How would you design a rate-limiting and queuing service using AWS Lambda and SQS to process millions of webhooks?

Where candidates lose points

Practice communicating out loud

During paired coding or mob programming rounds, interviewers evaluate how you express your ideas in real time. Explain your initial thoughts, trade-offs, and edge cases before writing code.

Focus on edge cases and testing

Always validate your solution with sample test inputs, including null values, empty collections, and boundary conditions, before declaring your code complete.

Master cloud and database fundamentals

Brush up on relational database indexing (MySQL) and fundamental AWS building blocks like Lambda, SQS, and S3, as these frequently appear in system design discussions.

Questions & practice

Implement a function to convert a Roman numeral to an integer.

Medium · Data Structures & 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?

Remove the N-th node from the end of a linked list in a single pass.

Medium · Data Structures & 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?

Write an implementation of the atoi function (converting a string to a 32-bit signed integer) with complete

Medium · Data Structures & Algorithms

Write an implementation of the atoi function (converting a string to a 32-bit signed integer) with complete edge-case handling.

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 an array of strings, write a program to count unique words efficiently while discussing time and space c

Medium · Data Structures & Algorithms

Given an array of strings, write a program to count unique words efficiently while discussing time and space complexity.

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?

Identify and implement a Binary Search Tree (BST) optimization for a given data lookup problem.

Medium · Data Structures & 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?

Stop tag and share joins from fanning out a page

Medium · join fan-out · semi-joins · many-to-many

resource_tag is (resource_id, tag_id) with PK (resource_id, tag_id); resource_share is (resource_id, shared_with_user_id, permission). The tagged-and-shared listing inner-joins resource to both, filters tenant_id, tag_id = ANY($2) and shared_with_user_id = $3, orders by updated_at DESC and takes 50. Pages come back with fewer than 50 distinct resources and the total in the header is far too high. Explain the row multiplication, rewrite both the page query and the count query so each is correct, and name the index each one needs. PostgreSQL 16.

Approach

1. Do the arithmetic against the predicates that are actually there. An inner join emits one row per matching child row, and both joins are filtered: tag_id = ANY($2) admits only the requested tags, shared_with_user_id = $3 admits one user's share rows. So a resource holding three of the requested tags and shared with $3 once yields three rows, not one — the multiplier is its count of matching tags times its share rows for that single user, and that second factor is 1 unless the table admits duplicate (resource_id, shared_with_user_id) pairs. LIMIT 50 then limits rows rather than resources, and COUNT(*) counts pairs — the header is the product, not the population.
2. Reject DISTINCT as the fix. It deduplicates after the product has been built, so the planner must materialise and sort the fanned-out set before the LIMIT can apply, and it leaves any SUM or AVG in the same select list wrong.
3. Rewrite both filters as semi-joins, keeping resource as the only row source: AND EXISTS (SELECT 1 FROM resource_tag rt WHERE rt.resource_id = r.resource_id AND rt.tag_id = ANY($2)) and the same shape against resource_share. A semi-join stops at the first match per resource and preserves the driving index order, so ORDER BY updated_at DESC, resource_id DESC LIMIT 50 still stops after 50 rows.
4. Count with the same predicates and no join at all: SELECT count(*) FROM resource r WHERE r.tenant_id = $1 AND r.status = 'active' AND EXISTS (...) AND EXISTS (...). Nothing multiplies a resource, so the number is the population.

Follow-up

• The filter changes from 'any of these tags' to 'all of these tags'. Rewrite it and state what it costs relative to the ANY form.
• A resource can be shared with the same user twice under different permissions. Does your count change, and should it?

Replace offset paging on the resource feed with keyset

Easy · keyset pagination · composite index · sort order

resource holds resource_id, tenant_id, owner_user_id, title, body_ref, version, status ('draft','active','archived','deleted'), created_at, updated_at, deleted_at, with an index on (tenant_id, status, updated_at DESC, resource_id DESC). The listing endpoint returns active resources for one tenant, newest update first, 50 per page, today with LIMIT 50 OFFSET n. Tenants reach page 400 and rows are created while they read. Write the keyset query, define what the cursor carries and how it is encoded, and say which part of the index each predicate uses. Assume PostgreSQL 16.

Approach

1. Name the two failures separately. OFFSET 20000 makes the server produce and discard 20,000 rows, so page cost grows with depth rather than with page size. Independently, any write that changes how many rows sort above the offset moves the window between two fetches, and the direction decides which anomaly you get: an insert lands at the head of updated_at DESC and pushes already-returned rows down past the boundary, so they are returned a second time; a delete above the offset, or a row whose updated_at is bumped above the cursor, pulls rows up and one is never returned at all. Nothing in the response reveals either.
2. Write the seek: WHERE tenant_id = $1 AND status = 'active' AND (updated_at, resource_id) < ($2, $3) ORDER BY updated_at DESC, resource_id DESC LIMIT 50. The row-value comparison is one index range rather than a disjunction, and both columns are NOT NULL, which is what makes that comparison well defined.
3. Map each predicate onto the index: tenant_id and status are equality on the leading columns, (updated_at, resource_id) is the range, and the ORDER BY matches the index order so no Sort node appears and the scan stops after 50 rows. The DESC in the definition only matters for mixed directions — a plain ascending btree on the same columns is read backwards for this query.
4. Put both sort columns in the cursor and nothing the client can tamper with into another tenant: base64 of (updated_at, resource_id), validated server-side, with tenant_id taken from the principal.

Follow-up

• The client asks for 'jump to page 400'. What do you offer instead, and what does the honest version cost?
• Sort order becomes user-selectable across four columns. How many indexes is that, and which would you refuse to add?

Design an automated cloud outage detector and alert system similar to AWS Health.

Medium · System Design & Infrastructure

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?

Architectural design for a high-traffic RESTful API service supporting real-time collaborative document update

Medium · System Design & Infrastructure

Architectural design for a high-traffic RESTful API service supporting real-time collaborative document updates.

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?

How would you design a rate-limiting and queuing service using AWS Lambda and SQS to process millions of webho

Medium · System Design & Infrastructure

How would you design a rate-limiting and queuing service using AWS Lambda and SQS to process millions of webhooks?

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?

Explain how you approach database schema design and indexing in MySQL for high-volume read/write operations.

Medium · System Design & Infrastructure

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?

Design an object-oriented domain model for a collaborative spreadsheet application with custom cell formulas.

Medium · Object-Oriented Design & Practical Codin

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?

Implement an API endpoint using language-specific idiomatic patterns and proper error handling structures.

Medium · Object-Oriented Design & Practical Codin

Approach

1. Say who the caller is and what they do when the call fails halfway.
2. Define the identity of a request so a retry cannot double-apply it.
3. Separate accepted, pending, failed and confirmed; they are different facts.
4. Design the error taxonomy before the success shape; callers branch on it.

Follow-up

• What happens if the caller retries after a timeout?
• How does a client discover it is on an old version of this contract?

How would you structure background job processing and event-driven messaging for enterprise integrations?

Medium · Object-Oriented Design & Practical Codin

Approach

1. Say who the caller is and what they do when the call fails halfway.
2. Define the identity of a request so a retry cannot double-apply it.
3. Separate accepted, pending, failed and confirmed; they are different facts.
4. Design the error taxonomy before the success shape; callers branch on it.

Follow-up

• What happens if the caller retries after a timeout?
• How does a client discover it is on an old version of this contract?

Write a clean class architecture to represent enterprise user permission hierarchies and role-based access con

Medium · Object-Oriented Design & Practical Codin

Write a clean class architecture to represent enterprise user permission hierarchies and role-based access control (RBAC).

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?

Walk me through your most complex technical project: what were the major architectural trade-offs?

Medium · Behavioral & Past Experience

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?

Read latency spikes on a sixty-second sawtooth

Medium · cache stampede · single-flight · ttl

The cached listing read path serves about 14k reads/second at an 85% hit rate. p99 sits at 35 ms for 57 seconds, jumps to 900 ms for 3, and repeats. During each spike the primary shows several hundred identical listing queries starting within the same millisecond, all carrying one large tenant's id. Cache entries use a 60-second TTL. Give the mechanism, the ordered checks, the fix, and the correctness hazard your fix must not introduce.

Approach

1. Match the period to a configured number before theorising about load. A spike every 60 seconds against a 60-second TTL is an entry expiring, and you confirm it by correlating spike timestamps with the entry's write time rather than with the traffic curve. If the period had matched a cron or a GC interval instead, this is a different investigation.
2. Establish the concurrency of the miss. Several hundred identical queries in one millisecond means the miss path has no coalescing: every request that arrives between expiry and repopulation recomputes. The herd size is that key's arrival rate times its recompute time, so at 1.2k reads/second for the hot key and a 250 ms recompute you expect about 300 concurrent misses, which matches what is observed.
3. Add single-flight on the miss path so one caller per key recomputes under a short-lived lock while the rest wait for its result. Prefer stale-while-revalidate where the read tolerates it: return the expired value immediately and refresh asynchronously, which removes the latency spike rather than serialising it into a queue of waiters.
4. De-synchronise the keys. Write TTLs with jitter, for example 60 seconds plus or minus 10%, so a deploy or a mass invalidation does not align every key on the same second and turn a per-key herd into a fleet-wide one.

Follow-up

• The same sawtooth appears on a key that is invalidated on write rather than expired. Is that the same bug?
• How does your answer change if the recompute takes 4 seconds instead of 250 ms?

Suggested practice checklist

Built from the rounds and topics Smartsheet candidates report.

Day 1 — Map the Smartsheet loop

• Write out the reported sequence: Recruiter Call, Technical Assessment, Technical Screen, Onsite Interview.
• 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 4 reported rounds, with the weakest marked.

Day 2 — Work System Design

• Spend the session on System Design, which Smartsheet candidates report being tested on.
• Write one worked example in System Design and time yourself on it.

Deliverable: One timed worked example in System Design.

Day 3 — Work Data Structures & Algorithms (DSA)

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

Deliverable: One timed worked example in Data Structures & Algorithms (DSA).

Day 4 — Work High-Traffic Scalability

• Spend the session on High-Traffic Scalability, which Smartsheet candidates report being tested on.
• Write one worked example in High-Traffic Scalability and time yourself on it.

Deliverable: One timed worked example in High-Traffic Scalability.

Day 5 — Answer out loud: Data Structures & Algorithms

• Answer aloud, timed: Implement a function to convert a Roman numeral to an integer.
• Answer aloud, timed: Remove the N-th node from the end of a linked list in a single pass.

Deliverable: Spoken answers to 2 reported Data Structures & Algorithms question(s), under time.

Day 6 — Answer out loud: System Design & Infrastructure

• Answer aloud, timed: Design an automated cloud outage detector and alert system similar to AWS Health.
• Answer aloud, timed: Architectural design for a high-traffic RESTful API service supporting real-time collaborative document updates.

Deliverable: Spoken answers to 2 reported System Design & Infrastructure question(s), under time.

Day 7 — Answer out loud: Object-Oriented Design & Practical Coding

• Answer aloud, timed: Design an object-oriented domain model for a collaborative spreadsheet application with custom cell formulas.
• Answer aloud, timed: Implement an API endpoint using language-specific idiomatic patterns and proper error handling structures.

Deliverable: Spoken answers to 2 reported Object-Oriented Design & Practical Coding question(s), under time.

Behavioural preparation

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

How do you handle scale, data consistency, and failover during high-traffic unexpected events?

Medium · System Design & Infrastructure

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?

Describe a situation where an unexpected technical issue occurred in production and how you diagnosed it.

Medium · Behavioral & Past Experience

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 handle situations where a senior stakeholder or teammate disagrees with your technical approach?

Medium · Behavioral & Past Experience

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?

Tell me about a time you had to deliver a critical feature under tight deadlines without compromising software

Medium · Behavioral & Past Experience

Tell me about a time you had to deliver a critical feature under tight deadlines without compromising software quality.

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?