Interview guides · Goldman Sachs Asset & Wealth Management
Goldman Sachs Asset & Wealth Management Software Engineer Interview Guide
Goldman Sachs Asset & Wealth Management Software Engineer interview guide: reported rounds, questions and how candidates describe the process.
The 60-second brief
As a Software Engineer within Goldman Sachs Asset & Wealth Management (AWM), you are at the intersection of high-frequency financial markets and complex client-facing technology. This division manages trillions in assets, and your work directly impacts how the firm delivers investment insights, manages risk, and provides tailored wealth solutions to institutional and individual clients. You will be building the platforms that power decision-making engines, portfolio management tools, and large-scale data processing systems. The role requires a rare combination of technical rigor and business acumen. You aren't just writing code; you are solving problems where latency, accuracy, and scalability are non-negotiable.
This guide is scoped to a Software Engineer candidate at Goldman Sachs Asset & Wealth Management.
Focus areas
- Data Structures & Algorithms (DSA)
- Problem Solving (Algorithmic Thinking)
- System Design
The Goldman Sachs Asset & Wealth Management interview process
Goldman Sachs Asset & Wealth Management candidates report 3 rounds over 3-5 weeks. The stages below are what candidates describe, not a published process.
Online Assessment
Initial technical filter through an online assessment.
What to demonstrate
- Initial technical filter through an online assessment
- Depth in Data Structures & Algorithms (DSA)
How to prepare
- Answer aloud and timed: How would you implement a Hash Map from scratch, and what are the trade-offs of different collision resolution strategies?
- Answer aloud and timed: Given an array of student marks, how do you find the highest marks or calculate the average efficiently?
Recruiter Screening
Discussion with a recruiter to assess fit for the role.
What to demonstrate
- Discussion with a recruiter to assess fit for the role
- Depth in Data Structures & Algorithms (DSA)
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.
Superday
A series of back-to-back interviews testing coding, design, and behavioral fit.
What to demonstrate
- A series of back-to-back interviews testing coding, design, and behavioral fit
- Depth in Data Structures & Algorithms (DSA)
How to prepare
- Answer aloud and timed: Describe how you would implement a Binary Tree right-view or perform a complex tree-based search.
- Answer aloud and timed: How would you design a URL shortener or a library management system from the ground up?
Where candidates lose points
Think out loud
Never code in silence. Your interviewer needs to understand your logic to grade you fairly, even if your final code has minor bugs.
Ask clarifying questions
Before you start coding, define the constraints. Ask about input sizes, edge cases, and expected outputs. This shows you are a thoughtful engineer.
Be ready for the "why
If you use a specific library or data structure, be prepared to explain why it is the best choice compared to the alternatives.
Research the firm
Understand the core business of Goldman Sachs Asset & Wealth Management. Knowing how your role fits into the broader mission of the firm can make your behavioral answers much more compelling.
Questions & practice
How would you implement a Hash Map from scratch, and what are the trade-offs of different collision resolution
Medium · Data Structures & Algorithms
How would you implement a Hash Map from scratch, and what are the trade-offs of different collision resolution strategies?
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 student marks, how do you find the highest marks or calculate the average efficiently?
Medium · Data Structures & 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?
Explain the logic behind a Graph traversal problem, such as finding the shortest path or detecting a cycle.
Medium · Data Structures & 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?
How would you merge two sorted arrays or lists while maintaining order?
Medium · Data Structures & 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?
Describe how you would implement a Binary Tree right-view or perform a complex tree-based search.
Medium · Data Structures & 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?
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?
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
- 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.
- 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.
- 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.
- 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?
How would you design a URL shortener or a library management system from the ground up?
Medium · System Design & 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?
What are the considerations for designing a system that requires high availability and low latency?
Medium · System Design & 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?
Explain the difference between horizontal and vertical scaling in the context of a high-traffic application.
Medium · System Design & 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?
How would you structure a class hierarchy to improve the maintainability of a legacy codebase?
Medium · System Design & 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?
Listing latency scales with page size, not with filters
Easy · n+1 · latency · query batching
The tenant listing endpoint reads resource filtered by tenant_id and status, ordered by updated_at DESC, and returns each row plus the owner's display name from app_user and the actor of that resource's latest resource_revision. p99 is 55 ms at 10 rows per page and 1.4 s at 200. Database telemetry shows 401 statements per request, each under 1 ms, and nothing in the slow-query log. Diagnose the cause and give the fix, stating the statement count per request and the p99 you expect afterwards.
Approach
- Read the counters before forming a theory. 401 statements for 200 rows is one driver query plus two per row, and sub-millisecond execution with an empty slow-query log rules out a bad plan. The time is round trips, which is why it is invisible in every per-query metric and scales with rows returned rather than with filter selectivity.
- Name the two per-row statements from their normalised text: a single-row app_user lookup by user_id, and a resource_revision lookup by resource_id ordered by version DESC LIMIT 1. Confirm by dropping those two response fields and watching the statement count fall to one. That locates the calls in the serialisation layer, not the repository.
- Check that the arithmetic accounts for the whole gap. Measure one round trip to the replica in isolation; 400 trips at roughly 3 ms of network plus 0.2 ms of execution is about 1.3 s on top of a 55 ms baseline, which matches. If the multiplication had fallen short, the N+1 would only be part of the story and you would keep looking.
- Batch both lookups. Collect owner_user_ids and resource_ids from the driver query, then issue WHERE tenant_id = $1 AND user_id = ANY($2) for the users, and PostgreSQL's SELECT DISTINCT ON (resource_id) ... WHERE resource_id = ANY($2) ORDER BY resource_id, version DESC for the latest revision, which the UNIQUE (resource_id, version) index serves directly. On an engine without DISTINCT ON, use a lateral join or a row_number window. Three statements per request at any page size.
Follow-up
- The page size is capped at 200 today. What breaks first if it is raised to 2,000, and is it still this bug?
- How do you stop the next N+1 from reaching production, given that no individual query is slow and the endpoint's tests pass?
Suggested practice checklist
Built from the rounds and topics Goldman Sachs Asset & Wealth Management candidates report.
Day 1 — Map the Goldman Sachs Asset & Wealth Management loop
- Write out the reported sequence: Online Assessment, Recruiter Screening, Superday.
- 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 & Algorithms (DSA)
- Spend the session on Data Structures & Algorithms (DSA), which Goldman Sachs Asset & Wealth Management candidates report being tested on.
- Write one worked example in Data Structures & Algorithms (DSA) and time yourself on it.
Deliverable: One timed worked example in Data Structures & Algorithms (DSA).
Day 3 — Work Problem Solving (Algorithmic Thinking)
- Spend the session on Problem Solving (Algorithmic Thinking), which Goldman Sachs Asset & Wealth Management candidates report being tested on.
- Write one worked example in Problem Solving (Algorithmic Thinking) and time yourself on it.
Deliverable: One timed worked example in Problem Solving (Algorithmic Thinking).
Day 4 — Work System Design
- Spend the session on System Design, which Goldman Sachs Asset & Wealth Management 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: Data Structures & Algorithms
- Answer aloud, timed: How would you implement a Hash Map from scratch, and what are the trade-offs of different collision resolution strategies?
- Answer aloud, timed: Given an array of student marks, how do you find the highest marks or calculate the average efficiently?
Deliverable: Spoken answers to 2 reported Data Structures & Algorithms question(s), under time.
Day 6 — Answer out loud: System Design & Architecture
- Answer aloud, timed: How would you design a URL shortener or a library management system from the ground up?
- Answer aloud, timed: How do you handle concurrency when multiple users attempt to access or update the same financial record?
Deliverable: Spoken answers to 2 reported System Design & Architecture question(s), under time.
Day 7 — Answer out loud: Behavioral & Situational
- Answer aloud, timed: Describe a time you faced a significant technical challenge; how did you arrive at a solution?
- Answer aloud, timed: How do you handle situations where you disagree with a teammate or manager on a technical approach?
Deliverable: Spoken answers to 2 reported Behavioral & Situational question(s), under time.
Behavioural preparation
Behavioural rounds judge the decision you made and what it cost.
How do you handle concurrency when multiple users attempt to access or update the same financial record?
Medium · System Design & 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?
Describe a time you faced a significant technical challenge; how did you arrive at a solution?
Medium · Behavioral & Situational
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 situations where you disagree with a teammate or manager on a technical approach?
Medium · Behavioral & Situational
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?
Can you explain a complex technical concept to a non-technical stakeholder?
Medium · Behavioral & Situational
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?
What draws you to Goldman Sachs Asset & Wealth Management, and how do you see your role contributing to the di
Medium · Behavioral & Situational
What draws you to Goldman Sachs Asset & Wealth Management, and how do you see your role contributing to the division's success?
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 you had to work under tight deadlines with limited resources.
Medium · Behavioral & Situational
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?