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McDonald's Software Engineer Interview Guide

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

The 60-second brief

The role of a Software Engineer at McDonald's is pivotal in driving the technological advancements that enhance the customer experience and streamline operations across our global network. You will be at the forefront of developing software solutions that power our digital platforms, drive efficiency in restaurant operations, and improve data analytics capabilities. This role is critical not only for ensuring that our systems are robust and efficient but also for innovating new ways to engage customers and improve their experience with McDonald's. As a Software Engineer, you will contribute to various products and systems, such as mobile applications, point-of-sale technologies, and backend services that support our extensive operations.

This guide is scoped to a Software Engineer candidate at McDonald's.

Focus areas

  • Coding Algorithms & Data Structures
  • Problem Solving
  • Timed Online Assessment (OA)

The McDonald's interview process

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

Application

Submit your application for the Software Engineer position.

What to demonstrate

  • Submit your application for the Software Engineer position
  • Depth in Coding Algorithms & Data Structures

How to prepare

  • Answer aloud and timed: Explain the differences between REST and SOAP APIs.
  • Answer aloud and timed: What are some common algorithms you use for data processing?

Initial Screening

Participate in initial screenings to assess fit for the role.

What to demonstrate

  • Participate in initial screenings to assess fit for the role
  • Depth in Coding Algorithms & Data Structures

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

Engage in technical assessments, which may include coding challenges.

What to demonstrate

  • Engage in technical assessments, which may include coding challenges
  • Depth in Coding Algorithms & Data Structures

How to prepare

  • Answer aloud and timed: Explain your thought process when tackling a coding challenge.
  • Answer aloud and timed: Demonstrate your familiarity with data structures, such as trees and graphs.

Final Interviews

Attend final interviews that may include behavioral assessments.

What to demonstrate

  • Attend final interviews that may include behavioral assessments
  • Depth in Coding Algorithms & Data Structures

How to prepare

  • Answer aloud and timed: Describe a time when you had to work under pressure. How did you handle it?
  • Answer aloud and timed: How do you prioritize your tasks when managing multiple projects?

Where candidates lose points

Research the Company

Understanding McDonald's history, values, and recent initiatives will help you align your answers with the company's mission.

Practice Coding Challenges

Utilize platforms like LeetCode or HackerRank to practice coding questions and refine your problem-solving skills.

Prepare for Behavioral Questions

Use the STAR method (Situation, Task, Action, Result) to structure your responses to behavioral questions effectively.

Show Enthusiasm

Express genuine interest in the role and company during your interviews. This can make a significant difference in how your candidacy is perceived.

Questions & practice

What are some common algorithms you use for data processing?

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?

Solve a common algorithm problem, such as reversing a string or finding duplicates in an 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?

Explain your thought process when tackling a coding challenge.

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?

Demonstrate your familiarity with data structures, such as trees and graphs.

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?

Explain why the owner filter ignores the listing index

Medium · composite index · query plans · sort elimination

The only index on resource is (tenant_id, status, updated_at DESC, resource_id DESC). A new endpoint returns one user's resources across all statuses, newest created first: WHERE tenant_id = $1 AND owner_user_id = $2 ORDER BY created_at DESC LIMIT 20. On a tenant with 2M rows it takes 900 ms and EXPLAIN shows a sort above a large scan. Explain precisely why the existing index cannot serve it, give the index that can, and state which of these the new index still will not help: owner_user_id alone across tenants; the same query ordered by updated_at. PostgreSQL 16.

Approach

  1. Separate the two jobs an index does. For filtering, a composite btree is seekable only on a left prefix, so with no predicate on status the scan can at best range over tenant_id and test owner_user_id per row; PostgreSQL 16 has no btree skip scan to jump the unconstrained column.
  2. For ordering, the index is sorted by (status, updated_at) within a tenant and not by created_at, so the LIMIT cannot stop early: every matching row is read and then sorted. That is the 'Sort Method: top-N heapsort' line, and it is why the plan reads 2M rows to answer with 20.
  3. Derive the replacement from the access path — equality, equality, then the ordering column: CREATE INDEX CONCURRENTLY ON resource (tenant_id, owner_user_id, created_at DESC). The scan seeks to the (tenant, owner) range and walks 20 entries in order, so the Sort node disappears along with the row-read.
  4. Treat INCLUDE (title, status) as conditional, not free. An index-only scan still visits the heap for any row whose page is not marked all-visible, so on a table taking 1.2k writes/second the win depends on autovacuum keeping the visibility map current, and the wider index costs more on every insert.

Follow-up

  • 90% of rows are status='active'. Would a partial index WHERE status = 'active' change your answer, and for which of the three queries?
  • A dashboard runs this for 40 owners in one page load. What changes about the design?

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?

Explain the differences between REST and SOAP APIs.

Medium · Technical / Domain Questions

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 design a scalable restaurant ordering system?

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?

What considerations would you take into account for database design in a high-traffic environment?

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?

Provide a solution for optimizing the performance of a slow application.

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?

How would you approach debugging a system that frequently crashes?

Medium · Problem-Solving / Case Studies

Approach

  1. Establish what changed and when, before forming any theory.
  2. Pick a bisection that eliminates candidates whichever way it turns out.
  3. Check the instrumentation before believing the symptom.
  4. Separate the trigger from the cause; the deploy is rarely the bug.

Follow-up

  • What would you look at first, and what would it rule out?
  • How would you tell a cause from a coincidence here?

Suggested practice checklist

Built from the rounds and topics McDonald's candidates report.

Day 1 — Map the McDonald's loop

  • Write out the reported sequence: Application, Initial Screening, Technical Assessment, Final Interviews.
  • 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 Coding Algorithms & Data Structures

  • Spend the session on Coding Algorithms & Data Structures, which McDonald's candidates report being tested on.
  • Write one worked example in Coding Algorithms & Data Structures and time yourself on it.

Deliverable: One timed worked example in Coding Algorithms & Data Structures.

Day 3 — Work Problem Solving

  • Spend the session on Problem Solving, which McDonald's 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 4 — Work Timed Online Assessment (OA)

  • Spend the session on Timed Online Assessment (OA), which McDonald's candidates report being tested on.
  • Write one worked example in Timed Online Assessment (OA) and time yourself on it.

Deliverable: One timed worked example in Timed Online Assessment (OA).

Day 5 — Answer out loud: Technical / Domain Questions

  • Answer aloud, timed: Explain the differences between REST and SOAP APIs.
  • Answer aloud, timed: What are some common algorithms you use for data processing?

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

Day 6 — Answer out loud: Coding / Algorithms

  • Answer aloud, timed: Solve a common algorithm problem, such as reversing a string or finding duplicates in an array.
  • Answer aloud, timed: Explain your thought process when tackling a coding challenge.

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

Day 7 — Answer out loud: Behavioral / Leadership

  • Answer aloud, timed: Describe a time when you had to work under pressure. How did you handle it?
  • Answer aloud, timed: How do you prioritize your tasks when managing multiple projects?

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

Behavioural preparation

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

Describe your experience with cloud computing platforms.

Medium · Technical / Domain Questions

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 time when you had to work under pressure. How did you handle 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 your tasks when managing 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?

Give an example of how you worked as part of a team to achieve a goal.

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?