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Electronic Arts (Ea) Software Engineer Interview Guide

Electronic Arts (Ea) Software Engineer interview guide: reported rounds, questions and how candidates describe the process.

The 60-second brief

As a Software Engineer at Electronic Arts (Ea), you are at the intersection of high-performance computing, creative innovation, and global scale. You are not just writing code; you are building the infrastructure, engines, and features that power some of the world’s most recognizable entertainment experiences. Whether you are working on rendering pipelines for major titles like Star Wars Jedi, optimizing anti-cheat systems, or developing AI-driven services in the EA Information Technology (EAIT) group, your work directly influences the player experience for millions of people. The environment at Electronic Arts (Ea) is deeply collaborative, requiring you to bridge the gap between technical complexity and artistic vision. You will work alongside designers, producers, and fellow engineers to translate ambitious ideas into stable, scalable software.

This guide is scoped to a Software Engineer candidate at Electronic Arts (Ea).

Focus areas

C++
Data structures
System design

The Electronic Arts (Ea) interview process

Electronic Arts (Ea) candidates report 3 rounds over 3-5 weeks. The stages below are what candidates describe, not a published process.

Recruiter Screening

Initial screening with a recruiter to discuss your background and assess role fit.

What to demonstrate

Initial screening with a recruiter to discuss your background and assess role fit
Depth in C++

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 Deep Dives

A series of technical sessions that may include live coding, architecture discussions, and code reviews.

What to demonstrate

A series of technical sessions that may include live coding, architecture discussions, and code reviews
Depth in C++

How to prepare

Answer aloud and timed: What are the primary performance considerations when working with Multi-threading?
Answer aloud and timed: Define Model-View-Controller (MVC) and its alternatives in system architecture.

Senior Role Interviews

For senior roles, additional interviews with directors or leadership to ensure alignment on vision and team contribution.

What to demonstrate

For senior roles, additional interviews with directors or leadership to ensure alignment on vision and team contribution
Depth in C++

How to prepare

Answer aloud and timed: Describe how you would handle Memory Fragmentation in a high-performance application.
Answer aloud and timed: Tell us about an accomplishment you are most proud of and the technical challenges you overcame.

Where candidates lose points

Talk through your process

Even if you know the answer immediately, explain your steps. Interviewers want to see how you approach problems, not just that you can reach the end result.

Understand the "Why

Don't just implement a feature; understand why it is being built and how it impacts the player. This is especially important for the Behavioral and Design rounds.

Ask meaningful questions

Use the time at the end of your interviews to ask about the team’s current technical challenges or the culture of the studio. This shows genuine engagement.

Be ready for C++ nuances

If you are applying for a game engine or core tech role, expect questions that go deep into object lifetimes and memory management.

Questions & practice

Explain the difference between Heap and Stack memory allocation.

Medium · Technical and Domain Expertise

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?

What are the primary performance considerations when working with Multi-threading?

Medium · Technical and Domain Expertise

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?

Describe how you would handle Memory Fragmentation in a high-performance application.

Medium · Technical and Domain Expertise

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?

Solve a problem involving Data Structures (e.g., Trees, Linked Lists, or Arrays).

Medium · Coding and Problem Solving

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?

Optimize a provided snippet of code for performance or readability.

Medium · Coding and Problem Solving

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?

Denormalise tenant onto revisions and backfill it live

Hard · denormalisation · online migration · backfill

resource_revision (revision_id, resource_id, version, actor_user_id, change_kind, patch, request_id, created_at) has 400M rows and no tenant column; tenant_id lives only on resource. Two reads need it: a tenant-scoped audit feed ordered by created_at DESC, and an offboarding purge. Both join back to resource today. Justify adding tenant_id to resource_revision against those two reads, name the anomaly the copy introduces and the constraint that prevents it, then give the ordered migration for a live table taking 1.2k writes/second — the lock each step takes, how the backfill is batched, and where each step stops being reversible. PostgreSQL 16.

Approach

Justify from the access path rather than from taste. Without the column, the audit feed either scans resource_revision by created_at and discards other tenants' rows, or resolves the tenant's resource_ids first and probes with them — both proportional to the tenant's whole history rather than to one page. With (tenant_id, created_at DESC, revision_id DESC) it is a seek that stops at 50 rows, and the purge becomes a ranged delete instead of a join.
Name the cost exactly: a second copy of a fact can disagree with the first. Make the disagreement unwritable rather than documented — add UNIQUE (resource_id, tenant_id) on resource so it can serve as a foreign-key target, then FOREIGN KEY (resource_id, tenant_id) REFERENCES resource (resource_id, tenant_id) on the revision table. A revision can then only ever carry its parent's tenant.
Step one, expand: ALTER TABLE resource_revision ADD COLUMN tenant_id BIGINT NULL, with no default, so it is a catalogue change and no rewrite. It still needs ACCESS EXCLUSIVE for an instant, and that instant queues behind the longest open transaction on the table while every later query queues behind it — set lock_timeout to 2s and retry rather than wait.
Step two, dual-write: deploy the writer that populates tenant_id on every new revision while reads still use the join. Reversible by redeploying the previous build, because nothing reads the column yet.

Follow-up

The backfill is half finished and a rollback is required. What state is the table in, and what does the previous build do with a half-populated column?
How do you verify the backfill actually finished, given rows are still being inserted while it runs?

Write the update path that detects a concurrent edit

Medium · optimistic concurrency · transactional outbox · audit history

resource carries version INT NOT NULL DEFAULT 1. resource_revision holds revision_id, resource_id, version, actor_user_id, change_kind, patch JSONB, request_id, created_at with UNIQUE (resource_id, version). outbox_event holds aggregate_type, aggregate_id, aggregate_version, event_type, payload, status. A PUT carries the version the client read. Write the exact statements for the single transaction that applies the edit, records the revision and enqueues 'resource.updated', and give the handler's branch on zero affected rows. Then say what PostgreSQL 16 does under READ COMMITTED when two of these updates hit one row at once.

Approach

One transaction, three writes, no network call inside it: UPDATE resource SET title = $3, version = version + 1, updated_at = now() WHERE resource_id = $1 AND tenant_id = $4 AND version = $2; then INSERT the resource_revision row at version $2 + 1; then INSERT the outbox_event row at the same aggregate_version. The event goes to a table rather than a broker because no transaction spans both.
Branch on the affected-row count before doing anything else. Zero has three causes — stale version, wrong tenant, row gone — so re-read once and map to 409 carrying the current version, or 404 for an id outside the caller's tenant, which also stops the endpoint confirming that another tenant's id exists.
State the engine behaviour instead of assuming it. Under READ COMMITTED the second UPDATE blocks on the row lock, and when the first commits PostgreSQL re-evaluates the WHERE clause against the newly committed row, so the version predicate now fails and the statement reports zero rows. Under REPEATABLE READ the identical collision raises SQLSTATE 40001 instead, so the handler must fold both shapes into one conflict response.
Keep UNIQUE (resource_id, version) even though the predicate already serialises writers. It is what makes a lost update unwritable if any other path ever reaches the revision table, and it converts a logic bug into 23505 rather than into a silently missing history row.

Follow-up

A client sends the version it read ten minutes ago and the resource has moved three versions. What is in your 409 so it can resolve the conflict without a full re-fetch?
Two editors, two disjoint fields, no overlap. Does your answer still refuse the second write, and should it?

How do you manage object lifetimes in C++ (e.g., constructors, destructors)?

Medium · Technical and Domain Expertise

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?

Define Model-View-Controller (MVC) and its alternatives in system architecture.

Medium · Technical and Domain Expertise

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?

Propose a solution to a design challenge (e.g., designing an API or a game feature).

Medium · Coding and Problem Solving

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?

Explain your approach to a System Design problem (e.g., designing a scalable service).

Medium · Coding and Problem Solving

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?

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

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.
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.
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.
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 Electronic Arts (Ea) candidates report.

Day 1 — Map the Electronic Arts (Ea) loop

Write out the reported sequence: Recruiter Screening, Technical Deep Dives, Senior Role 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 3 reported rounds, with the weakest marked.

Day 2 — Work C++

Spend the session on C++, which Electronic Arts (Ea) candidates report being tested on.
Write one worked example in C++ and time yourself on it.

Deliverable: One timed worked example in C++.

Day 3 — Work Data structures

Spend the session on Data structures, which Electronic Arts (Ea) candidates report being tested on.
Write one worked example in Data structures and time yourself on it.

Deliverable: One timed worked example in Data structures.

Day 4 — Work System design

Spend the session on System design, which Electronic Arts (Ea) 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 5 — Answer out loud: Technical and Domain Expertise

Answer aloud, timed: Explain the difference between Heap and Stack memory allocation.
Answer aloud, timed: How do you manage object lifetimes in C++ (e.g., constructors, destructors)?

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

Day 6 — Answer out loud: Behavioral and Leadership

Answer aloud, timed: Tell us about an accomplishment you are most proud of and the technical challenges you overcame.
Answer aloud, timed: How do you handle disagreements with stakeholders regarding project deadlines or features?

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

Day 7 — Answer out loud: Coding and Problem Solving

Answer aloud, timed: Solve a problem involving Data Structures (e.g., Trees, Linked Lists, or Arrays).
Answer aloud, timed: Propose a solution to a design challenge (e.g., designing an API or a game feature).

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