Garena Software Engineer Interview Guide

The 60-second brief

As a Software Engineer at Garena, you are at the core of delivering high-performance gaming experiences to millions of users globally. You will be responsible for building, scaling, and maintaining the robust systems that power our flagship titles and digital entertainment platforms. Your work directly influences product stability, game performance, and the seamless integration of services that keep our community connected. This role is both technically demanding and strategically significant. You will often work on high-concurrency systems, complex backend infrastructures, and performance-critical services that must operate with high availability. Because Garena operates at a global scale, the problems you solve—from optimizing networking protocols to designing efficient database schemas—have a tangible impact on the user experience.

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

Focus areas

• Data Structures (DSA)
• Algorithms (Problem Solving)
• Coding Interviews

The Garena interview process

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

Assessment Phase

Begin with an online coding test or a written technical paper covering core CS concepts.

What to demonstrate

• Begin with an online coding test or a written technical paper covering core CS concepts
• Depth in Data Structures (DSA)

How to prepare

• Answer aloud and timed: Implement a specific sorting algorithm from scratch.
• Answer aloud and timed: Given a list of numbers, find the most efficient way to sort them.

Technical Interviews

Participate in a series of technical interviews with engineers and team leads.

What to demonstrate

• Participate in a series of technical interviews with engineers and team leads
• Depth in Data Structures (DSA)

How to prepare

• Answer aloud and timed: How would you implement a queue or stack using basic data structures?
• Answer aloud and timed: Write a function to manipulate a linked list or a binary tree.

Manager Discussion

Conclude with a discussion with a manager or department head.

What to demonstrate

• Conclude with a discussion with a manager or department head
• Depth in Data Structures (DSA)

How to prepare

• Answer aloud and timed: Solve a classic problem involving string manipulation or array traversal.
• Answer aloud and timed: Describe the TCP three-way handshake process.

Where candidates lose points

Review the Fundamentals

Revisit your undergraduate CS notes on OS, networking, and databases. These are often tested in paper-based or technical screen rounds.

Communicate Your Process

Never stay silent while coding. Talk through your logic so the interviewer can follow your thought process, which is often as important as the code itself.

Be Prepared for "Why

Don't just implement a solution; be ready to defend why you chose that particular data structure or algorithm over alternatives.

Practice Live Coding

Whether it’s a whiteboard or a shared document, practice writing code without the help of IDE features like autocomplete.

Research the Product

Understand the scale and nature of Garena’s gaming platforms. Being able to relate your technical solutions to the company’s actual products shows genuine interest and insight.

Questions & practice

Implement a specific sorting algorithm from scratch.

Medium · Algorithms and Data Structures

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 list of numbers, find the most efficient way to sort them.

Medium · Algorithms and Data Structures

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 queue or stack using basic data structures?

Medium · Algorithms and Data Structures

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 manipulate a linked list or a binary tree.

Medium · Algorithms and Data Structures

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 classic problem involving string manipulation or array traversal.

Medium · Algorithms and Data Structures

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 how memory allocation works (heap vs. stack) in C/C++.

Medium · System Fundamentals and Networking

Approach

1. Say what the runtime actually does before reasoning about the code.
2. Name what is shared across threads and what owns each piece of state.
3. Identify the window where an invariant is briefly untrue.
4. 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?

Why do you want to join Garena?

Medium · Behavioral and Role-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?

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?

Describe the TCP three-way handshake process.

Medium · System Fundamentals and Networking

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 do you defend against DDoS attacks?

Medium · System Fundamentals and Networking

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?

Explain the difference between TCP and UDP and when to use each.

Medium · System Fundamentals and Networking

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 does a database master-slave replication process work?

Medium · System Fundamentals and Networking

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 do you approach designing a scalable feature or application?

Medium · Behavioral and Role-Fit

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?

Edge instances grow 400 MB per hour until the nightly restart

Hard · memory leak · heap analysis · metric cardinality

Edge API instances start at 700 MB resident and grow about 400 MB/hour; a nightly rolling restart has hidden it for weeks. Growth continues unchanged when request rate halves overnight, p99 degrades in the last hours before an instance is recycled, and heap used immediately after a forced full GC rises monotonically. The service holds no product state. Name the discriminating measurement that separates the plausible causes, give the most likely cause, and give the fix and how you would verify it.

Approach

1. Separate resident memory from live heap first, because they fail differently. Resident size can grow from fragmentation, native buffers or thread stacks while the heap is flat; heap used after a full GC rising monotonically is the measurement that says objects are reachable and not being released. You already have it, so this is retention, not fragmentation, and that closes off half the candidate list.
2. Use the rate's independence from traffic as the discriminator. Growth that continues at half the request rate rules out per-request objects that are merely slow to collect and points at a structure that grows with distinct values observed rather than with call volume. Write the candidates that have that property: a metrics registry keyed on a high-cardinality label, an unevicted cache, an interner, a per-key lock map.
3. Take two heap snapshots an hour apart and diff by retained size, reading the dominator tree, not by allocation count or instance count. Expect one root holding a map with millions of entries, then follow the reference chain to the code that inserts and never removes. Allocation profilers point at churn, which is the wrong signal here.
4. The candidate that fits this service is an observability label carrying an identifier, such as a request path recorded before templating so that /v1/resources/48213 becomes its own metric series. That grows with distinct ids seen, is independent of rate, and explains the late p99 degradation, since GC cost rises with the size of the live set.

Follow-up

• Post-GC heap is now flat but resident size still creeps. What are you looking at, and does it matter?
• How would you have detected this before an OOM, given the nightly restart masked the trend?

Suggested practice checklist

Built from the rounds and topics Garena candidates report.

Day 1 — Map the Garena loop

• Write out the reported sequence: Assessment Phase, Technical Interviews, Manager Discussion.
• 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 (DSA)

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

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

Day 3 — Work Algorithms (Problem Solving)

• Spend the session on Algorithms (Problem Solving), which Garena 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 Garena 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: Algorithms and Data Structures

• Answer aloud, timed: Implement a specific sorting algorithm from scratch.
• Answer aloud, timed: Given a list of numbers, find the most efficient way to sort them.

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

Day 6 — Answer out loud: System Fundamentals and Networking

• Answer aloud, timed: Describe the TCP three-way handshake process.
• Answer aloud, timed: How do you defend against DDoS attacks?

Deliverable: Spoken answers to 2 reported System Fundamentals and Networking question(s), under time.

Day 7 — Answer out loud: Behavioral and Role-Fit

• Answer aloud, timed: Why do you want to join Garena?
• Answer aloud, timed: Tell us about a technical challenge you faced and how you resolved it.

Deliverable: Spoken answers to 2 reported Behavioral and Role-Fit question(s), under time.

Behavioural preparation

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

Tell us about a technical challenge you faced and how you resolved it.

Medium · Behavioral and Role-Fit

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 disagreements within a technical team?

Medium · Behavioral and Role-Fit

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 your experience with specific technologies (e.g., Python, MySQL, Nginx).

Medium · Behavioral and Role-Fit

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?