As a Software Engineer at Stefanini Brasil, you are at the intersection of global technological innovation and localized business transformation. You will be responsible for designing, developing, and maintaining robust software solutions that empower large-scale clients, often within the financial, retail, or public sectors. Your work directly impacts how these enterprises manage their infrastructure, serve their customers, and scale their digital operations. This role requires a blend of technical precision and adaptability. Whether you are working on legacy system migrations, cloud-native development, or integrating complex third-party APIs, your contribution is critical to the delivery of high-performance software. You will operate in a dynamic, project-based environment where your ability to translate business requirements into clean, scalable code defines your success and the value provided to our clients. ##### Tip Stefanini Brasil often acts as a partner to major enterprises, meaning you may be interviewed by both internal technical leadership and the client’s own development or management teams.
HR Screen
reportedInitial assessment focusing on cultural and professional fit.
What to demonstrate
- Initial assessment focusing on cultural and professional fit
- Depth in Java
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 Evaluation
reportedIn-depth technical evaluations to assess candidate's skills.
What to demonstrate
- In-depth technical evaluations to assess candidate's skills
- Depth in Java
How to prepare
- Answer aloud and timed: Describe your experience with REST API design and the appropriate use of HTTP verbs.
- Answer aloud and timed: How do you approach unit testing and ensure code quality in a fast-paced environment?
Client Meeting
reportedFinal meeting with representatives from the client organization.
What to demonstrate
- Final meeting with representatives from the client organization
- Depth in Java
How to prepare
- Answer aloud and timed: Can you explain the SOLID principles and provide a real-world example of how you applied them?
- Answer aloud and timed: How would you design a scalable service using AWS (e.g., Lambda, DynamoDB, API Gateway)?
2 candidate reports. Individual accounts describe a particular role and hiring cycle.
Stefanini Brasil Software Engineer interview: client architecture discussion
I began with an alignment conversation with HR, then interviewed with technical leadership. After that, I was introduced to a client. The role would be in a financial context, so the conversation stayed close to the kinds of decisions and architecture I had worked on before. The technical part was light but still required clear explanations. I was asked about choices I had made in an earlier hack…
Read full experienceStefanini Brasil Software Engineer interview: organic and conversational process
The interview unfolded in a fairly organic way. There were different moments, a few pauses, relaxed conversations, and varied questions along the way. I answered naturally and did not feel as though I was being interrogated. My impressions became clearer as the discussion moved forward. Overall, the process continued normally to the end, with balanced expectations. I left with the sense that the…
Read full experiencePracHub editorial advice for the preparation topics above.
Own your projects
Be prepared to discuss in detail any project you list on your resume. You should be able to justify every architectural choice you made.
Be honest about your limits
If you don't know the answer to a deep technical question, it is better to explain your approach to finding the answer rather than guessing.
Stay persistent
Follow-up is important. If you don't hear back within the promised timeframe, a polite, professional follow-up is expected.
Choose a category, try a prompt, then open its approach, worked solution or follow-up when you need it.
Explain the difference between Task and Thread in asynchronous programming.
Explain the difference between Task and Thread in asynchronous programming.
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?
Archive a resource graph without breaking live references or recursing
Resources reference other resources within a tenant; for the largest tenant the reference table holds up to 2,000,000 nodes and 8,000,000 edges. Archiving a resource must archive everything reachable from it that nothing outside the set still references, refuse when a live external referrer exists, and terminate when references form cycles, which they legitimately do. Produce the archive order and the refusal list, targeting O(V+E). Say what stops the traversal crossing a tenant boundary, and why recursion is the wrong control structure at this size.
Approach
- Load the subgraph with the tenant predicate on both endpoints of the edge, not only on the side you started from. Scoping the left table alone is the classic cross-tenant leak: one mis-entered edge then pulls another tenant's resources into the traversal and, worse, into the archive.
- Traverse iteratively with an explicit stack. A 2,000,000-node graph can hold a chain deep enough to exhaust a native stack in the low tens of thousands of frames, and that failure is a process crash rather than an error you can return.
- Treat cycles as data rather than corruption: compute strongly connected components with Tarjan in O(V+E) using its own explicit stack, then condense. The condensation is a DAG, so a topological order over it gives the archive order, and every member of a component archives in one transaction because no order within a cycle is valid.
- Decide refusals with reverse edges. A candidate is archivable only if every in-edge originates inside the candidate set, so build the transpose or count in-degrees restricted to the visited set, and emit each blocked resource with the id of the external referrer, which is the only part of the answer an operator can act on.
Follow-up
- The graph is read in one query and the archive writes a minute later. What can change in between, and how do you make the write safe?
- The candidate set is 400,000 resources. Is that one transaction, and if not, what does a half-finished archive look like to a reader?
Identify the heaviest tenants in a five-minute window under memory pressure
The edge service handles about 3,000 requests per second across roughly 50,000 tenants, peaking near 9,000. Expose the 50 heaviest tenants by request count over the trailing five minutes so limits can be tightened before one tenant's backfill starves the fleet. You may not retain five minutes of raw records. Give the exact solution and its memory, then the bounded-memory approximation with its error stated as a formula, and say which you would ship and at what tenant cardinality that choice changes.
Approach
- Do the exact version first, because it is affordable at this cardinality: a ring of 300 one-second counters per tenant, advanced lazily, is 1,200 bytes of counters per tenant and roughly 60 to 90 MB for 50,000 tenants with overhead. Carry a running total and subtract the bucket you overwrite so a window read is O(1) rather than 300 adds.
- Extract the top 50 with a size-k min-heap over the tenant sums: O(d log k) for d tenants, against O(d log d) to sort them all. Maintaining the heap continuously instead of on query requires a tenant-to-heap-index map, because incrementing a count already inside the heap means sifting from a known position, and without that map you rebuild the heap on every request.
- State the approximation precisely rather than gesturing at sketches. Misra-Gries with m counters retains every item whose true count exceeds N/(m+1), and each retained count underestimates the truth by at most N/(m+1). With m = 1,000 and N = 900,000 requests in the window the error is roughly 900 requests, which is fine for spotting a tenant sending 50,000 and useless for ranking two tenants 200 apart.
- Say what breaks when the window slides: Misra-Gries and Space-Saving are insert-only and cannot be decremented as records age out. The workable construction is one summary per sub-window, say ten seconds, with 30 summaries merged at query time, and the merged error is the sum of the per-summary errors, so the bound degrades linearly in the number of sub-windows.
Follow-up
- The heaviest tenant is heavy because of one export job rather than user traffic. Should the limiter treat those as the same tenant?
- Two tenants sit tied at the boundary of the top 50. Does your answer flap, and does the flapping matter?
Replace offset paging on the resource feed with keyset
resource holds resource_id, tenant_id, owner_user_id, title, body_ref, version, status ('draft','active','archived','deleted'), created_at, updated_at, deleted_at, with an index on (tenant_id, status, updated_at DESC, resource_id DESC). The listing endpoint returns active resources for one tenant, newest update first, 50 per page, today with LIMIT 50 OFFSET n. Tenants reach page 400 and rows are created while they read. Write the keyset query, define what the cursor carries and how it is encoded, and say which part of the index each predicate uses. Assume PostgreSQL 16.
Approach
- Name the two failures separately. OFFSET 20000 makes the server produce and discard 20,000 rows, so page cost grows with depth rather than with page size. Independently, any write that changes how many rows sort above the offset moves the window between two fetches, and the direction decides which anomaly you get: an insert lands at the head of updated_at DESC and pushes already-returned rows down past the boundary, so they are returned a second time; a delete above the offset, or a row whose updated_at is bumped above the cursor, pulls rows up and one is never returned at all. Nothing in the response reveals either.
- Write the seek: WHERE tenant_id = $1 AND status = 'active' AND (updated_at, resource_id) < ($2, $3) ORDER BY updated_at DESC, resource_id DESC LIMIT 50. The row-value comparison is one index range rather than a disjunction, and both columns are NOT NULL, which is what makes that comparison well defined.
- Map each predicate onto the index: tenant_id and status are equality on the leading columns, (updated_at, resource_id) is the range, and the ORDER BY matches the index order so no Sort node appears and the scan stops after 50 rows. The DESC in the definition only matters for mixed directions — a plain ascending btree on the same columns is read backwards for this query.
- Put both sort columns in the cursor and nothing the client can tamper with into another tenant: base64 of (updated_at, resource_id), validated server-side, with tenant_id taken from the principal.
Follow-up
- The client asks for 'jump to page 400'. What do you offer instead, and what does the honest version cost?
- Sort order becomes user-selectable across four columns. How many indexes is that, and which would you refuse to add?
Find version gaps and relay lag with window functions
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
- 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.
- 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.
- 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.
- 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?
How do you manage service lifetimes and dependency injection in your applications?
How do you manage service lifetimes and dependency injection in your applications?
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 your experience with REST API design and the appropriate use of HTTP verbs.
Describe your experience with REST API design and the appropriate use of HTTP verbs.
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?
How do you approach unit testing and ensure code quality in a fast-paced environment?
How do you approach unit testing and ensure code quality in a fast-paced environment?
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?
Can you explain the SOLID principles and provide a real-world example of how you applied them?
Can you explain the SOLID principles and provide a real-world example of how you applied them?
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 service using AWS (e.g., Lambda, DynamoDB, API Gateway)?
How would you design a scalable service using AWS (e.g., Lambda, DynamoDB, API Gateway)?
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 trade-offs between different database architectures for high-traffic applications?
What are the trade-offs between different database architectures for high-traffic applications?
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 a complex technical challenge you faced and the architectural decisions you made to resolve it.
Describe a complex technical challenge you faced and the architectural decisions you made to resolve it.
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 Stefanini Brasil candidates report.
Prepare, practise & reflect
One practical outcome each day. Spend longer where you need it.
0 / 7 done01Map the Stefanini Brasil loop
- Write out the reported sequence: HR Screen, Technical Evaluation, Client Meeting.
- 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 Stefanini Brasil candidates report being tested on.
- Write one worked example in Java and time yourself on it.
Deliverable: One timed worked example in Java.
03Work Angular
- Spend the session on Angular, which Stefanini Brasil candidates report being tested on.
- Write one worked example in Angular and time yourself on it.
Deliverable: One timed worked example in Angular.
04Work REST APIs / REST API design
- Spend the session on REST APIs / REST API design, which Stefanini Brasil candidates report being tested on.
- Write one worked example in REST APIs / REST API design and time yourself on it.
Deliverable: One timed worked example in REST APIs / REST API design.
05Answer out loud: Technical Proficiency & Domain Knowledge
- Answer aloud, timed: Explain the difference between Task and Thread in asynchronous programming.
- Answer aloud, timed: How do you manage service lifetimes and dependency injection in your applications?
Deliverable: Spoken answers to 2 reported Technical Proficiency & Domain Knowledge question(s), under time.
06Answer out loud: Architecture & System Design
- Answer aloud, timed: How would you design a scalable service using AWS (e.g., Lambda, DynamoDB, API Gateway)?
- Answer aloud, timed: What are the trade-offs between different database architectures for high-traffic applications?
Deliverable: Spoken answers to 2 reported Architecture & System Design question(s), under time.
07Answer out loud: Behavioral & Professional Alignment
- Answer aloud, timed: Tell us about a time you had to learn a new technology on the fly to meet a project deadline.
- Answer aloud, timed: How do you handle feedback from a client or a team lead when your approach is challenged?
Deliverable: Spoken answers to 2 reported Behavioral & Professional Alignment 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.
How do you handle data consistency and error handling in distributed systems?
How do you handle data consistency and error handling in distributed systems?
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 us about a time you had to learn a new technology on the fly to meet a project deadline.
Tell us about a time you had to learn a new technology on the fly to meet a project deadline.
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 feedback from a client or a team lead when your approach is challenged?
How do you handle feedback from a client or a team lead when your approach is challenged?
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 prioritize tasks under pressure.
Describe a situation where you had to prioritize tasks under pressure.
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?
Why do you want to work on projects within the Stefanini Brasil ecosystem?
Why do you want to work on projects within the Stefanini Brasil ecosystem?
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
How do you handle data consistency and error handling in distributed systems?
- 02
Tell us about a time you had to learn a new technology on the fly to meet a project deadline.
- 03
How do you handle feedback from a client or a team lead when your approach is challenged?
- 04
Describe a situation where you had to prioritize tasks under pressure.
How difficult are the technical interviews?
Difficulty varies by project, but expect a focus on practical application rather than theoretical trivia. You will be asked about the decisions you made in past projects.
Stefanini Brasil Software Engineer candidate reports ↗What is the typical timeline for the process?
The process can be quite rapid, often moving from HR contact to offer in under two weeks. However, coordination with external clients can sometimes lead to scheduling delays.
Stefanini Brasil Software Engineer candidate reports ↗Is there a coding test?
Yes, many roles involve either a live technical discussion, a take-home challenge, or a review of your previous projects on GitHub.
Stefanini Brasil Software Engineer candidate reports ↗How should I prepare for the client interview?
Treat the client interview as a professional consultation. Focus on demonstrating how your expertise will solve their specific business problems.
Stefanini Brasil Software Engineer candidate reports ↗What topics does Stefanini Brasil test in interviews?
Stefanini Brasil interviews most often cover Communication Skills, Stakeholder Management, Stakeholder Communication, Java, and Scrum. The exact emphasis depends on the specific role you apply for.
Stefanini Brasil 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.
- 01Stefanini Brasil 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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