At Rakuten Advertising, a Software Engineer plays a pivotal role in driving the technological backbone of global affiliate marketing, programmatic advertising, and media solutions. You will be responsible for building, scaling, and maintaining high-performance, low-latency systems that process billions of daily transactions and tracking events. The engineering division handles massive data pipelines and real-time bidding infrastructure where system efficiency and reliability directly impact global brands and publishers. As a Software Engineer, you will collaborate with cross-functional teams to deliver robust backend systems, intuitive user interfaces, and seamless integration APIs. The engineering culture at Rakuten Advertising values clean code, test-driven development, and proactive problem-solving. Whether you are optimizing a database query to handle concurrent requests or refactoring a core microservice, your work will directly influence the performance and scalability of our advertising technology ecosystem. This role requires a unique blend of deep technical expertise, algorithmic thinking, and a passion for building resilient software. You will work with modern technologies, including,, cloud-native infrastructure, and relational/non-relational databases. Joining this team means tackling complex distributed systems challenges where performance is measured in milliseconds and scale is truly global.
HR Phone Screening
reportedInitial call to review your background and discuss your career interests.
What to demonstrate
- Initial call to review your background and discuss your career interests
- Depth in Coding Interviews
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 Screening
reportedDeeper technical assessment that may include a live discussion, coding assessment, or take-home assignment.
What to demonstrate
- Deeper technical assessment that may include a live discussion, coding assessment, or take-home assignment
- Depth in Coding Interviews
How to prepare
- Answer aloud and timed: Explain the difference between average-case and worst-case time complexity for common sorting algorithms.
- Answer aloud and timed: Given an array of integers, find the contiguous subarray that has the largest sum.
Virtual Onsite Loop
reportedComprehensive virtual interviews covering algorithmic coding, system design, and behavioral assessments.
What to demonstrate
- Comprehensive virtual interviews covering algorithmic coding, system design, and behavioral assessments
- Depth in Coding Interviews
How to prepare
- Answer aloud and timed: Implement an algorithm to reverse a linked list both iteratively and recursively.
- Answer aloud and timed: Explain how dependency injection works in Spring Boot and how it helps in writing testable code.
PracHub editorial advice for the preparation topics above.
Clarify take-home requirements early
If your process includes a take-home assignment, make sure you fully understand the expectations and constraints before you begin writing code.
Some candidates have reported receiving assignments that did not fully align with their primary skillsets
If you notice a mismatch—such as a frontend task for a backend role—proactively discuss this with your recruiter before starting the assignment.
Master Java concurrency basics
Be ready to discuss how Java handles multi-threading, synchronization, and memory management under the hood.
Choose a category, try a prompt, then open its approach, worked solution or follow-up when you need it.
Write a program to identify and remove duplicates from a list, and explain the time and space complexity of yo
Write a program to identify and remove duplicates from a list, and explain the time and space complexity of your approach.
Approach
- Restate the input: its shape, its size, and what is guaranteed about it.
- Name the brute-force solution and its complexity before improving on it.
- Choose the data structure from the access pattern, not from familiarity.
- 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 handle concurrency and prevent race conditions when updating a shared resource in a multi-thread
How would you handle concurrency and prevent race conditions when updating a shared resource in a multi-threaded application?
Approach
- Say what the runtime actually does before reasoning about the code.
- Name what is shared across threads and what owns each piece of state.
- Identify the window where an invariant is briefly untrue.
- Distinguish a value from a reference to it, and say which one you handed out.
Follow-up
- What happens if two callers reach this at the same time?
- Where could this allocate more than you expect?
Explain the difference between average-case and worst-case time complexity for common sorting algorithms.
Explain the difference between average-case and worst-case time complexity for common sorting algorithms.
Approach
- Restate the input: its shape, its size, and what is guaranteed about it.
- Name the brute-force solution and its complexity before improving on it.
- Choose the data structure from the access pattern, not from familiarity.
- 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 integers, find the contiguous subarray that has the largest sum.
Given an array of integers, find the contiguous subarray that has the largest sum.
Approach
- Restate the input: its shape, its size, and what is guaranteed about it.
- Name the brute-force solution and its complexity before improving on it.
- Choose the data structure from the access pattern, not from familiarity.
- 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 reverse a linked list both iteratively and recursively.
Implement an algorithm to reverse a linked list both iteratively and recursively.
Approach
- Restate the input: its shape, its size, and what is guaranteed about it.
- Name the brute-force solution and its complexity before improving on it.
- Choose the data structure from the access pattern, not from familiarity.
- 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 how you would optimize a slow-running database query in a production environment.
Explain how you would optimize a slow-running database query in a production environment.
Approach
- Name the grain you start from and join outward from it.
- Check whether any join is one-to-many before aggregating, or the sums inflate.
- Say which index the query would use, and what makes it unusable.
- 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?
Why do you want to join Rakuten Advertising, and how does your background align with our advertising technolog
Why do you want to join Rakuten Advertising, and how does your background align with our advertising technology focus?
Approach
- Name the grain you start from and join outward from it.
- Check whether any join is one-to-many before aggregating, or the sums inflate.
- Say which index the query would use, and what makes it unusable.
- 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?
Explain how dependency injection works in Spring Boot and how it helps in writing testable code.
Explain how dependency injection works in Spring Boot and how it helps in writing testable code.
Approach
- Clarify what is being asked and what a complete answer contains.
- State your assumptions explicitly before working the problem.
- Say what you would check first and why it is the highest-information step.
- 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 do you secure REST APIs against common vulnerabilities like unauthorized access or injection attacks?
How do you secure REST APIs against common vulnerabilities like unauthorized access or injection attacks?
Approach
- Say who the caller is and what they do when the call fails halfway.
- Define the identity of a request so a retry cannot double-apply it.
- Separate accepted, pending, failed and confirmed; they are different facts.
- 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?
Describe the lifecycle of a bean in the Spring container.
Describe the lifecycle of a bean in the Spring container.
Approach
- Clarify what is being asked and what a complete answer contains.
- State your assumptions explicitly before working the problem.
- Say what you would check first and why it is the highest-information step.
- Work from the requirement backwards to the design.
Follow-up
- What assumption would you test first?
- How would you know your answer was wrong?
What are the differences between optimistic and pessimistic locking, and when would you use each?
What are the differences between optimistic and pessimistic locking, and when would you use each?
Approach
- Clarify what is being asked and what a complete answer contains.
- State your assumptions explicitly before working the problem.
- Say what you would check first and why it is the highest-information step.
- 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 scalable tracking API that receives millions of click events per hour?
How would you design a scalable tracking API that receives millions of click events per hour?
Approach
- Fix the scope first: who calls this, how often, and what they do when it fails.
- Name the read and write paths separately; they rarely have the same bottleneck.
- Choose a partition key and say what query it makes expensive.
- 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 rate-limiting system to protect downstream microservices from being overwhelmed by traffic spikes.
Design a rate-limiting system to protect downstream microservices from being overwhelmed by traffic spikes.
Approach
- Fix the scope first: who calls this, how often, and what they do when it fails.
- Name the read and write paths separately; they rarely have the same bottleneck.
- Choose a partition key and say what query it makes expensive.
- 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 do you approach database schema design for a system that requires both high-write throughput and complex r
How do you approach database schema design for a system that requires both high-write throughput and complex read queries?
Approach
- Fix the scope first: who calls this, how often, and what they do when it fails.
- Name the read and write paths separately; they rarely have the same bottleneck.
- Choose a partition key and say what query it makes expensive.
- 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 implement a distributed caching strategy to reduce database load.
Describe how you would implement a distributed caching strategy to reduce database load.
Approach
- Fix the scope first: who calls this, how often, and what they do when it fails.
- Name the read and write paths separately; they rarely have the same bottleneck.
- Choose a partition key and say what query it makes expensive.
- 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 do you ensure high availability and fault tolerance in a microservices-based architecture?
How do you ensure high availability and fault tolerance in a microservices-based architecture?
Approach
- Fix the scope first: who calls this, how often, and what they do when it fails.
- Name the read and write paths separately; they rarely have the same bottleneck.
- Choose a partition key and say what query it makes expensive.
- 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
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
- 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.
- 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.
- 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.
- 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?
Built from the rounds and topics Rakuten Advertising candidates report.
Prepare, practise & reflect
One practical outcome each day. Spend longer where you need it.
0 / 7 done01Map the Rakuten Advertising loop
- Write out the reported sequence: HR Phone Screening, Technical Screening, 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 3 reported rounds, with the weakest marked.
02Work Coding Interviews
- Spend the session on Coding Interviews, which Rakuten Advertising 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.
03Work Java
- Spend the session on Java, which Rakuten Advertising candidates report being tested on.
- Write one worked example in Java and time yourself on it.
Deliverable: One timed worked example in Java.
04Work Spring Boot
- Spend the session on Spring Boot, which Rakuten Advertising candidates report being tested on.
- Write one worked example in Spring Boot and time yourself on it.
Deliverable: One timed worked example in Spring Boot.
05Answer out loud: Coding & Algorithmic Problem Solving
- Answer aloud, timed: Write a program to identify and remove duplicates from a list, and explain the time and space complexity of your approach.
- Answer aloud, timed: How would you handle concurrency and prevent race conditions when updating a shared resource in a multi-threaded application?
Deliverable: Spoken answers to 2 reported Coding & Algorithmic Problem Solving question(s), under time.
06Answer out loud: Backend Development & Frameworks
- Answer aloud, timed: Explain how dependency injection works in Spring Boot and how it helps in writing testable code.
- Answer aloud, timed: How do you secure REST APIs against common vulnerabilities like unauthorized access or injection attacks?
Deliverable: Spoken answers to 2 reported Backend Development & Frameworks question(s), under time.
07Answer out loud: System Design & Architecture
- Answer aloud, timed: How would you design a scalable tracking API that receives millions of click events per hour?
- Answer aloud, timed: Design a rate-limiting system to protect downstream microservices from being overwhelmed by traffic spikes.
Deliverable: Spoken answers to 2 reported System Design & Architecture question(s), under time.
Expand any day for tasks and deliverables. Your progress is saved on this device.
Behavioural rounds judge the decision you made and what it cost.
Walk me through your resume and highlight a project where you had to solve a highly complex technical challeng
Walk me through your resume and highlight a project where you had to solve a highly complex technical challenge.
Approach
- Pick a story where you made the decision, not one where you watched it.
- State the situation in two sentences and spend the rest on the reasoning.
- Give the blast radius: what could have broken, and what you measured.
- 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 when you had a disagreement with a team member regarding a technical decision. How did yo
Tell me about a time when you had a disagreement with a team member regarding a technical decision. How did you resolve it?
Approach
- Pick a story where you made the decision, not one where you watched it.
- State the situation in two sentences and spend the rest on the reasoning.
- Give the blast radius: what could have broken, and what you measured.
- 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 you had to work under tight deadlines with incomplete requirements. How did you pri
Describe a situation where you had to work under tight deadlines with incomplete requirements. How did you prioritize your tasks?
Approach
- Pick a story where you made the decision, not one where you watched it.
- State the situation in two sentences and spend the rest on the reasoning.
- Give the blast radius: what could have broken, and what you measured.
- 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?
Share an experience where you identified and resolved a performance bottleneck in a production system.
Share an experience where you identified and resolved a performance bottleneck in a production system.
Approach
- Pick a story where you made the decision, not one where you watched it.
- State the situation in two sentences and spend the rest on the reasoning.
- Give the blast radius: what could have broken, and what you measured.
- 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?
- 01
Walk me through your resume and highlight a project where you had to solve a highly complex technical challenge.
- 02
Tell me about a time when you had a disagreement with a team member regarding a technical decision. How did you resolve it?
- 03
Describe a situation where you had to work under tight deadlines with incomplete requirements. How did you prioritize your tasks?
- 04
Share an experience where you identified and resolved a performance bottleneck in a production system.
How difficult is the interview process for a Software Engineer?
The interview process is generally rated as moderate to difficult. It requires a strong grasp of computer science fundamentals, coding proficiency, and the ability to design scalable systems. Focused preparation on core Java concepts and system design patterns is highly recommended.
Rakuten Advertising Software Engineer candidate reports ↗What is the primary programming language used in the interviews?
While Java is highly preferred due to our core technology stack, candidates are generally allowed to use any modern programming language of their choice (such as Python, C++, or Go) during the algorithmic coding rounds.
Rakuten Advertising Software Engineer candidate reports ↗Does the interview process involve a take-home assignment?
Depending on the specific team and role level, you may be asked to complete a take-home programming assignment. This assignment typically focuses on building a functional backend service and evaluates your code structure, concurrency handling, and testing practices.
Rakuten Advertising Software Engineer candidate reports ↗How long does the entire interview process take?
Rakuten Advertising is known for a relatively quick and efficient interview process. For many candidates, the entire process—from the initial recruiter screen to the final offer decision—is completed within 2 to 3 weeks.
Rakuten Advertising Software Engineer candidate reports ↗Is the work environment hybrid or fully remote?
The working model depends on the specific office location and team requirements. Many of our offices, such as San Mateo and Toronto, operate on a hybrid model, combining in-office collaboration days with remote work flexibility.
Rakuten Advertising Software Engineer candidate reports ↗What topics does Rakuten Advertising test in interviews?
Rakuten Advertising interviews most often cover Coding Interviews, SQL, Account Executive (AE) Sales Role, Marketing analytics, and Java. The exact emphasis depends on the specific role you apply for.
Rakuten Advertising Software Engineer candidate reports ↗Sources & methodology 3 sources ↗
No official company page is cited. Rounds and questions come from candidate reports and PracHub editorial material; each source shows the date it was read.
- 01Rakuten Advertising Software Engineer candidate reports ↗
Company-reported rounds, questions and FAQ.
Candidate reports · Accessed 2026-09-22 - 02PracHub Software Engineer practice ↗
PracHub practice material, not company-reported.
PracHub page · Accessed 2026-09-22 - 03PracHub preparation framework ↗
PracHub preparation guidance.
PracHub page · Accessed 2026-09-22
Explore related engineering environments and compare the preparation focus.
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