As a Software Engineer at Ernst & Young U.S. LLP (EY), you are not merely writing code; you are building the technological infrastructure that enables global business transformation. You will operate at the intersection of high-stakes consulting and cutting-edge software development, delivering scalable solutions that address complex challenges for clients across diverse industries. Your work directly impacts how organizations manage data, automate processes, and modernize their digital ecosystems. This role requires a unique blend of technical expertise and a consultative mindset. You will often work in collaborative, cross-functional teams to translate ambiguous business requirements into robust, production-ready software. Whether you are developing microservices, optimizing system performance, or architecting new platforms, your contributions will be central to the firm’s commitment to building a better working world. The environment is fast-paced, intellectually demanding, and offers significant exposure to enterprise-level architecture.
Screening Round
reportedInitial evaluation to assess candidate's fit for the role.
What to demonstrate
- Initial evaluation to assess candidate's fit for the role
- Depth in Java
How to prepare
- Answer aloud and timed: Explain the core principles of OOP and how they apply to your recent projects.
- Answer aloud and timed: Describe the difference between ArrayList and LinkedList and when to use each.
Technical Assessments
reportedOne or more assessments that may include coding, system design, or case studies.
What to demonstrate
- One or more assessments that may include coding, system design, or case studies
- Depth in Java
How to prepare
- Answer aloud and timed: What are the key features of Java 8 that you use frequently?
- Answer aloud and timed: Explain the concept of Circuit Breaker in the context of microservices.
Managerial Discussion
reportedFinal discussion with management to evaluate overall fit and alignment with company culture.
What to demonstrate
- Final discussion with management to evaluate overall fit and alignment with company culture
- Depth in Java
How to prepare
- Answer aloud and timed: How do you identify and resolve production memory outage issues?
- Answer aloud and timed: Walk me through a challenging technical issue you faced in a recent project and how you resolved it.
PracHub editorial advice for the preparation topics above.
Own your resume
Every line on your resume is fair game. Be prepared to explain the technical challenges you faced in every project listed.
Think out loud
During coding or case study rounds, communicate your thought process clearly. Interviewers want to see how you approach ambiguity.
Focus on the "Why
Don't just explain what you did; explain why you chose that specific approach over alternatives.
Be professional
Despite reports of varying interview experiences, maintain a high level of professional courtesy and patience throughout every interaction.
Choose a category, try a prompt, then open its approach, worked solution or follow-up when you need it.
How do you identify and resolve production memory outage issues?
How do you identify and resolve production memory outage issues?
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?
Walk me through a challenging technical issue you faced in a recent project and how you resolved it.
Walk me through a challenging technical issue you faced in a recent project and how you resolved it.
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 do you approach optimizing the performance of an application?
How do you approach optimizing the performance of an application?
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?
If you were tasked with building a feature from scratch, what is your design process?
If you were tasked with building a feature from scratch, what is your design process?
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?
Keep soft-deleted accounts from blocking re-registration
app_user holds user_id, tenant_id, email CITEXT, password_hash (NULL for SSO principals), email_verified_at, auth_version, status ('invited','active','suspended','deactivated'), created_at, updated_at, deleted_at. Two live accounts for one address inside a tenant must be impossible, but an address freed by a soft delete must be reusable, and the same tenant may delete and re-register it repeatedly. Write the uniqueness DDL for PostgreSQL 16, then the equivalent for MySQL 8 where partial indexes do not exist, and say what each permits once three deleted rows already hold that address.
Approach
- Start from what is actually unique: not (tenant_id, email), but (tenant_id, email) among live rows. PostgreSQL says that directly — CREATE UNIQUE INDEX app_user_live_email ON app_user (tenant_id, email) WHERE deleted_at IS NULL. A full constraint over the same two columns burns the address permanently the first time someone deletes an account.
- Keep case-insensitivity in the type or the index, never in the application: CITEXT as given, or UNIQUE (tenant_id, lower(email)) as an expression index where the extension is unavailable. A case-sensitive unique column is exactly how two accounts for one human appear.
- For MySQL 8 the predicate has to move inside the key: add a discriminator column that is a constant 0 while the row is live and is set to user_id on delete, with UNIQUE (tenant_id, email, deleted_marker). Live rows share the constant and still collide; deleted rows differ from each other and stop colliding.
- State the NULL variant and its dependency: leaving the marker NULL for deleted rows also works, because a unique index treats NULLs as distinct — true in MySQL, and true in PostgreSQL only under the default NULLS DISTINCT, which PostgreSQL 15 lets you reverse. Check the polarity against the three existing deleted rows: constant-on-live is what preserves the collision you want, and reversing it silently admits duplicate live accounts.
Follow-up
- A deleted account re-registers with the same address the next day. Do the old resource rows follow the new user_id, and how does the API keep the two principals apart?
- How do you honour an erasure request while resource_revision.actor_user_id still references this table?
Hold a per-tenant active cap against concurrent creates
A tenant on the standard plan may hold at most 50 resources with status='active'. The create handler runs SELECT count(*) FROM resource WHERE tenant_id = $1 AND status = 'active', compares to 50, then inserts. Two creates arrive 3 ms apart on different instances and the tenant lands at 51. Name the anomaly, say whether PostgreSQL 16 READ COMMITTED or REPEATABLE READ prevents it and why, then give an implementation that holds the cap at READ COMMITTED with the exact statements. Finally, say what changes when the cap is 'at most one running export per tenant' on job_run.
Approach
- Name it: write skew. The two transactions read an overlapping set and write disjoint rows, so there is no row-level conflict for the engine to detect and each commit is individually legal.
- Rule out the levels precisely. READ COMMITTED takes a fresh snapshot per statement and takes no lock on the counted rows, so both see 49. PostgreSQL's REPEATABLE READ is snapshot isolation: it removes non-repeatable reads and phantoms within the snapshot but still admits write skew, because the anomaly is not a re-read of a changed row, it is a read of a set that a concurrent transaction invalidates. Only SERIALIZABLE closes it, by tracking the read dependency and aborting one transaction with SQLSTATE 40001 — a guarantee that exists only if the application re-runs the whole transaction from the read.
- Convert the set predicate into a single-row conflict: keep tenant.active_resource_count and run UPDATE tenant SET active_resource_count = active_resource_count + 1 WHERE tenant_id = $1 AND active_resource_count < 50 in the same transaction as the INSERT. Zero affected rows is the cap, returned as 409. The row lock serialises the decision at any isolation level, and contention is bounded to one tenant's row — which is also the fair-scheduling unit, unlike a global counter that would convoy every tenant behind one row.
- State the cost you just took on: a counter is a second source of truth that can drift, so every path that changes status must adjust it inside the same transaction, and a periodic reconciliation has to exist, with resource_revision as the authority for what the count should have been.
Follow-up
- A resource moves from archived back to active. Which statements change, and what breaks if the counter update and the status change land in different transactions?
- The cap becomes plan-dependent and a plan can change mid-month. Where does the number 50 live, and who reads it?
Explain the core principles of OOP and how they apply to your recent projects.
Explain the core principles of OOP and how they apply to your recent projects.
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?
Describe the difference between ArrayList and LinkedList and when to use each.
Describe the difference between ArrayList and LinkedList and when to 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?
What are the key features of Java 8 that you use frequently?
What are the key features of Java 8 that you use frequently?
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?
Explain the concept of Circuit Breaker in the context of microservices.
Explain the concept of Circuit Breaker in the context of microservices.
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?
Edge instances grow 400 MB per hour until the nightly restart
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
- 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.
- 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.
- 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.
- 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?
Built from the rounds and topics Ernst & Young U.S. LLP candidates report.
Prepare, practise & reflect
One practical outcome each day. Spend longer where you need it.
0 / 7 done01Map the Ernst & Young U.S. LLP loop
- Write out the reported sequence: Screening Round, Technical Assessments, Managerial 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.
02Work Java
- Spend the session on Java, which Ernst & Young U.S. LLP candidates report being tested on.
- Write one worked example in Java and time yourself on it.
Deliverable: One timed worked example in Java.
03Work Core Java (fundamentals)
- Spend the session on Core Java (fundamentals), which Ernst & Young U.S. LLP candidates report being tested on.
- Write one worked example in Core Java (fundamentals) and time yourself on it.
Deliverable: One timed worked example in Core Java (fundamentals).
04Work Object-Oriented Programming (OOP)
- Spend the session on Object-Oriented Programming (OOP), which Ernst & Young U.S. LLP candidates report being tested on.
- Write one worked example in Object-Oriented Programming (OOP) and time yourself on it.
Deliverable: One timed worked example in Object-Oriented Programming (OOP).
05Answer out loud: Technical Fundamentals and Core Java
- Answer aloud, timed: Explain the core principles of OOP and how they apply to your recent projects.
- Answer aloud, timed: Describe the difference between ArrayList and LinkedList and when to use each.
Deliverable: Spoken answers to 2 reported Technical Fundamentals and Core Java question(s), under time.
06Answer out loud: Project Experience and Scenario-Based Problem Solving
- Answer aloud, timed: Walk me through a challenging technical issue you faced in a recent project and how you resolved it.
- Answer aloud, timed: How do you approach optimizing the performance of an application?
Deliverable: Spoken answers to 2 reported Project Experience and Scenario-Based Problem Solving question(s), under time.
07Dry run for Ernst & Young U.S. LLP
- Run one full mock under time, then write down the two questions you most want to ask your interviewers.
Deliverable: A completed timed mock and two questions to ask.
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.
Tell me about a time you had to deal with a difficult client requirement while maintaining code quality.
Tell me about a time you had to deal with a difficult client requirement while maintaining code quality.
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?
How do you handle disagreements within your development team regarding technical architecture?
How do you handle disagreements within your development team regarding technical architecture?
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?
Argue against a design, lose, and commit anyway
Describe a design you argued against and lost. State the failure you predicted as a named mechanism, not a feeling about complexity: two services that would need one transaction, a projection with no rebuild path, a write path with no idempotency key. Say what evidence you brought, what the decision maker weighed instead, and what you did after the decision was made: what you instrumented, what you wrote down, and whether the prediction came true. Five minutes.
Approach
- State the prediction in falsifiable form up front: the mechanism, the condition that triggers it, and the observable outcome. A prediction that cannot be checked also cannot be credited to you later.
- Show the evidence you had at the time and label each piece honestly as measured, analogous, or intuition. Keeping the intuition is fine; disguising it as data is the thing that erodes your standing in the next argument.
- Represent the opposing case at full strength, including the constraint you did not control: a fixed date, a team boundary, or the fact that the decision was cheap to reverse and yours was not.
- Make disagree-and-commit concrete. Name the artefact you left behind so the prediction could be settled without you: the alert and its threshold, the counter on the dashboard, the decision note that recorded the trade-off and the condition that would revisit it.
Follow-up
- What threshold on that alert would have proved you right, and did anyone ever look at it?
- If the same proposal arrived tomorrow with the same deadline, would you argue it the same way?
- 01
Tell me about a time you had to deal with a difficult client requirement while maintaining code quality.
- 02
How do you handle disagreements within your development team regarding technical architecture?
- 03
Describe a design you argued against and lost. State the failure you predicted as a named mechanism, not a feeling about complexity: two services that would need one transaction, a projection with no rebuild path, a write path with no idempotency key. Say what evidence you brought, what the decision maker weighed instead, and what you did after the decision was made: what you instrumented, what you wrote down, and whether the prediction came true. Five minutes.
How should I prepare for the technical assessment?
Focus on LeetCode medium-level problems and practical, scenario-based coding. Many candidates find that practicing Java fundamentals and Spring Boot configurations is more beneficial than focusing solely on competitive programming.
Ernst & Young U.S. LLP Software Engineer candidate reports ↗What is the most important trait for a candidate at EY?
A combination of technical competence and a "consultant mindset." You must be able to explain your technical decisions in the context of business requirements and client impact.
Ernst & Young U.S. LLP Software Engineer candidate reports ↗How long does the process take?
The duration varies, but many candidates report a timeline of 30 days. Stay proactive in your follow-ups, but remain patient, as the process involves multiple layers of internal review. ##### Tip If you are asked about your experience with a specific tool, be honest about your level of expertise. It is better to explain how you learn new technologies than to overstate your current knowledge.
Ernst & Young U.S. LLP Software Engineer candidate reports ↗What topics does Ernst & Young U.S. LLP test in interviews?
Ernst & Young U.S. LLP interviews most often cover Java, Python, Problem Solving, Spring Boot, and SQL. The exact emphasis depends on the specific role you apply for.
Ernst & Young U.S. LLP Software Engineer candidate reports ↗What roles can I prepare for at Ernst & Young U.S. LLP?
LLP, including AI Engineer, Business Analyst, Consultant, and Data Analyst, and more.
Ernst & Young U.S. LLP 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.
- 01Ernst & Young U.S. LLP 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
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