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Zendesk Software Engineer Interview Guide

Zendesk Software Engineer interview guide: reported rounds, questions and how candidates describe the process.

The 60-second brief

A Software Engineer at Zendesk plays a critical role in building and scaling the world's leading customer experience (CX) platform. The products you build and maintain—such as Zendesk Support, Zendesk Chat, and the AI-powered Solve suite—enable over 100,000 businesses globally to communicate seamlessly with their customers. This is a high-impact position where the code you write directly influences the daily workflows of millions of agents and shapes the customer service experiences of billions of consumers. At Zendesk, engineering is not just about writing code in isolation; it is about managing massive scale, complexity, and real-time reliability. You will work on distributed systems, microservices architectures, and robust APIs that must handle billions of requests daily with minimal latency.

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

Focus areas

  • Data Structures & Algorithms (DSA)
  • Zendesk API
  • Problem Solving

The Zendesk interview process

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

Initial Conversation

Begin with a conversation with a technical recruiter to discuss your background.

What to demonstrate

  • Begin with a conversation with a technical recruiter to discuss your background
  • Depth in Data Structures & Algorithms (DSA)

How to prepare

  • Answer aloud and timed: Implement a function to reverse the words in a string in-place, and write comprehensive unit tests for it.
  • Answer aloud and timed: Write a program to solve a variation of the standard FizzBuzz problem, and explain how you would structure unit tests to validate the solution.

Hiring Manager Screen

Screen with a hiring manager to discuss your background and high-level technical interests.

What to demonstrate

  • Screen with a hiring manager to discuss your background and high-level technical interests
  • Depth in Data Structures & Algorithms (DSA)

How to prepare

  • Prepare two projects you led end to end, each with the decision you owned and what it cost.
  • Have three questions about the team's roadmap and how success is measured in the first six months.

Practical Assessment

Complete a take-home assignment or online coding assessment reflecting real-world tasks.

What to demonstrate

  • Complete a take-home assignment or online coding assessment reflecting real-world tasks
  • Depth in Data Structures & Algorithms (DSA)

How to prepare

  • Answer aloud and timed: Create a basic client application using React that consumes a public API and renders a user-friendly interface.
  • Answer aloud and timed: Build a command-line interface (CLI) application that interacts with the Zendesk API to retrieve and display support ticket data.

Virtual Onsite Loop

Participate in multiple focused sessions covering pair programming, system design, and behavioral evaluations.

What to demonstrate

  • Participate in multiple focused sessions covering pair programming, system design, and behavioral evaluations
  • Depth in Data Structures & Algorithms (DSA)

How to prepare

  • Answer aloud and timed: Write a parser to ingest, validate, and clean badly formed JSON data from an external API efficiently.
  • Answer aloud and timed: Design and implement an asynchronous service that makes multiple API calls, processes the responses, and logs errors gracefully.

Where candidates lose points

Focus on Object-Oriented Design (OOD)

While algorithmic efficiency matters, Zendesk interviewers place a high premium on clean object-oriented design, proper separation of concerns, and code readability.

Treat the Take-Home Seriously

The take-home assignment is often the foundation for your subsequent technical interviews. Ensure your submission is well-structured, thoroughly tested, and includes a clear README explaining your design decisions and how to run the code.

Communicate Constantly

During live coding and pair programming sessions, do not code in silence. Explain your approach, discuss trade-offs, and ask for feedback. Interviewers want to see how you collaborate as a teammate.

Align with Zendesk Values

Be ready to discuss how you practice empathy, champion diversity, and foster collaboration in your daily work. These values are deeply integrated into the behavioral evaluation process.

Questions & practice

Implement a function to reverse the words in a string in-place, and write comprehensive unit tests for it.

Medium · Coding and Algorithmic Problem-Solving

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 program to solve a variation of the standard FizzBuzz problem, and explain how you would structure uni

Medium · Coding and Algorithmic Problem-Solving

Write a program to solve a variation of the standard FizzBuzz problem, and explain how you would structure unit tests to validate the solution.

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 input stream of data, write an algorithm to parse and sort the records based on specific criteria.

Medium · Coding and Algorithmic Problem-Solving

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?

Implement an algorithm to search for specific patterns within a dataset, and discuss the time and space comple

Medium · Coding and Algorithmic Problem-Solving

Implement an algorithm to search for specific patterns within a dataset, and discuss the time and space complexity of your approach.

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?

Why do you want to join Zendesk, and how do you see your skills contributing to our engineering culture?

Medium · Behavioral & Culture Fit

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?

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?

Create a basic client application using React that consumes a public API and renders a user-friendly interface

Medium · Take-Home & Practical Engineering

Create a basic client application using React that consumes a public API and renders a user-friendly interface.

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?

Build a command-line interface (CLI) application that interacts with the Zendesk API to retrieve and display s

Medium · Take-Home & Practical Engineering

Build a command-line interface (CLI) application that interacts with the Zendesk API to retrieve and display support ticket data.

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 parser to ingest, validate, and clean badly formed JSON data from an external API efficiently.

Medium · Take-Home & Practical Engineering

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?

Design and implement an asynchronous service that makes multiple API calls, processes the responses, and logs

Medium · Take-Home & Practical Engineering

Design and implement an asynchronous service that makes multiple API calls, processes the responses, and logs errors gracefully.

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?

Model a software system or microservice that handles high-volume event logging and real-time data streaming.

Medium · System Design & Architecture

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 a simplified version of a ticket management system like Zendesk Support, detailing your database schema

Medium · System Design & Architecture

Design a simplified version of a ticket management system like Zendesk Support, detailing your database schema and API endpoints.

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?

Explain how you would refactor a monolithic application into a microservices-based architecture without causin

Medium · System Design & Architecture

Explain how you would refactor a monolithic application into a microservices-based architecture without causing downtime.

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?

Describe how you would handle rate limiting, caching, and data consistency across distributed systems.

Medium · System Design & Architecture

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?

p99 jumped on one listing filter while p50 stayed flat

Medium · query planning · composite index · percentiles

After a release that added an owner_user_id filter to the resource listing, p99 rose from 90 ms to 1.9 s while p50 stayed at 40 ms. Traffic and row counts are unchanged. resource carries the index (tenant_id, status, updated_at DESC, resource_id DESC). The new query filters tenant_id and owner_user_id, orders by updated_at DESC, resource_id DESC, and takes 20 rows. On PostgreSQL, explain the shape of the regression, prove it from a query plan, and give the index you would add.

Approach

  1. Start from the shape. A flat p50 with a moved p99 means a subset of requests changed cost, not all of them, so the first job is naming the subset. Bucket the endpoint's latency by the tenant's row count; the natural hypothesis is that large tenants are a small share of requests and all of the tail.
  2. Get the plan for the new query on a large tenant with EXPLAIN (ANALYZE, BUFFERS). Expect an index scan over the tenant's range, a filter discarding most of it, then a Sort feeding the Limit, possibly reporting Sort Method: external merge Disk. Read actual rows on the scan node, not estimated.
  3. Explain why the existing index cannot serve it. A composite B-tree is seekable only as a left prefix, and with no equality predicate on status the scan cannot treat updated_at as an ordering, because rows in the tenant's range are ordered by status first. Everything matching must be read and sorted before LIMIT 20 can apply, so a tenant with 400,000 rows pays 400,000 rows to return 20.
  4. Add (tenant_id, owner_user_id, updated_at DESC, resource_id DESC). Equality on the first two columns leaves the index ordered by updated_at within that pair, so the plan becomes an index scan that stops after 20 rows with no Sort node. PostgreSQL can scan a B-tree backwards, so the DESC markers matter only if the two sort columns ever disagree in direction; keeping them explicit documents the order the keyset cursor depends on.

Follow-up

  • The endpoint paginates with OFFSET. What does page 500 cost with your index, and what does the keyset version cost?
  • How would you have caught this before release, given that a 10,000-row seed database produces the same plan shape at an unnoticeable cost?

Suggested practice checklist

Built from the rounds and topics Zendesk candidates report.

Day 1 — Map the Zendesk loop

  • Write out the reported sequence: Initial Conversation, Hiring Manager Screen, Practical Assessment, Virtual Onsite Loop.
  • 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 Data Structures & Algorithms (DSA)

  • Spend the session on Data Structures & Algorithms (DSA), which Zendesk 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 3 — Work Zendesk API

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

Deliverable: One timed worked example in Zendesk API.

Day 4 — Work Problem Solving

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

Deliverable: One timed worked example in Problem Solving.

Day 5 — Answer out loud: Coding and Algorithmic Problem-Solving

  • Answer aloud, timed: Implement a function to reverse the words in a string in-place, and write comprehensive unit tests for it.
  • Answer aloud, timed: Write a program to solve a variation of the standard FizzBuzz problem, and explain how you would structure unit tests to validate the solution.

Deliverable: Spoken answers to 2 reported Coding and Algorithmic Problem-Solving question(s), under time.

Day 6 — Answer out loud: Take-Home & Practical Engineering

  • Answer aloud, timed: Create a basic client application using React that consumes a public API and renders a user-friendly interface.
  • Answer aloud, timed: Build a command-line interface (CLI) application that interacts with the Zendesk API to retrieve and display support ticket data.

Deliverable: Spoken answers to 2 reported Take-Home & Practical Engineering question(s), under time.

Day 7 — Answer out loud: System Design & Architecture

  • Answer aloud, timed: Model a software system or microservice that handles high-volume event logging and real-time data streaming.
  • Answer aloud, timed: Design a simplified version of a ticket management system like Zendesk Support, detailing your database schema and API endpoints.

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

Behavioural preparation

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

Describe a time when you had a significant technical disagreement with a teammate or lead. How did you resolve

Medium · Behavioral & Culture Fit

Describe a time when you had a significant technical disagreement with a teammate or lead. How did you resolve it?

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?

Talk about a challenging project from your resume. What key technical decisions did you make, and what did you

Medium · Behavioral & Culture Fit

Talk about a challenging project from your resume. What key technical decisions did you make, and what did you learn from the failures?

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 a situation where a critical production system goes down, and you are tasked with resolving

Medium · Behavioral & Culture Fit

How do you handle a situation where a critical production system goes down, and you are tasked with resolving the issue under pressure?

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?