As a Software Engineer at Sundew, you are at the heart of our technical operations. You are responsible for building, maintaining, and scaling the robust platforms that define our competitive edge in the market. Whether you are working on high-performance infrastructure or crafting seamless user interfaces, your work directly impacts our ability to deliver value to our clients. This role is uniquely critical to Sundew because we operate at the intersection of high-scale infrastructure and complex application development. You will be expected to solve multifaceted problems that require both deep technical expertise and a pragmatic, business-oriented mindset. Success here means you are not just writing code; you are architecting solutions that support our long-term growth and technical stability.
Technical Background Screening
reportedInitial assessment of the candidate's technical background to ensure alignment with the role.
What to demonstrate
- Initial assessment of the candidate's technical background to ensure alignment with the role
- Depth in MEAN Stack
How to prepare
- Answer aloud and timed: Explain the core differences between monolithic and microservices architectures in the context of high-traffic applications.
- Answer aloud and timed: How do you approach optimizing database queries for applications with significant latency requirements?
Deep-Dive Technical Assessments
reportedIn-depth technical evaluations to assess coding skills and problem-solving abilities.
What to demonstrate
- In-depth technical evaluations to assess coding skills and problem-solving abilities
- Depth in MEAN Stack
How to prepare
- Answer aloud and timed: Describe a scenario where you had to debug a production issue in a complex environment; what was your systematic process?
- Answer aloud and timed: What are the primary security considerations you prioritize when designing an API?
Team-Fit Discussions
reportedConversations with engineering peers and management to evaluate cultural and team alignment.
What to demonstrate
- Conversations with engineering peers and management to evaluate cultural and team alignment
- Depth in MEAN Stack
How to prepare
- Answer aloud and timed: How do you stay current with evolving frameworks, and how do you decide when to adopt a new technology for a production project?
- Answer aloud and timed: How would you design a system to handle a sudden, massive spike in concurrent user traffic?
PracHub editorial advice for the preparation topics above.
Communicate your thought process
We are more interested in how you approach a problem than in seeing a perfect solution immediately.
Ask clarifying questions
Before jumping into a solution, ensure you understand the constraints and business requirements of the problem.
Review your past projects
Be ready to explain the "why" behind the architectural decisions you made in your previous roles.
Stay pragmatic
Always consider the trade-offs of your technical choices, such as performance vs. maintainability.
Choose a category, try a prompt, then open its approach, worked solution or follow-up when you need it.
Find overlapping job attempts and peak concurrency from lease records
A day of job_run history yields about 50,000,000 attempt records: (job_run_id, job_type, attempt, started_at, finished_at which is NULL when the worker died, lease_expires_at). Leases expire on a clock, so a job that outran its lease ran twice. Produce (a) every job_run_id whose attempts overlapped in wall-clock time and (b) the peak number of simultaneously running attempts per job_type with the minute it occurred. Target O(n log n). State how you treat a NULL finished_at and what clock skew does to your answer.
Approach
- Define the interval before sorting anything: an attempt occupies [started_at, COALESCE(finished_at, lease_expires_at)). finished_at is observed and lease_expires_at is only a promise, so every attempt without a finish contributes an estimate and the whole result is a lower bound on overlap rather than an exact count.
- For peak concurrency, sweep: emit 2n endpoints, sort by (timestamp, kind) with ends ordered before starts at equal timestamps, then walk the sequence maintaining a counter per job_type and record each type's maximum with its timestamp. O(n log n) dominated by the sort, O(n) space, or O(1) extra if the sort is external and the walk streams.
- For overlap detection, do not compare attempts pairwise. A single global sort by (job_run_id, started_at) gives both the grouping and the order; within a group, keep the maximum end seen so far and report an overlap exactly when the next start is less than that running maximum, which is one linear pass after the sort.
- Half-open intervals matter and are easy to get wrong: with closed intervals an attempt ending at the same millisecond another begins reads as concurrency two, and across 50,000,000 records that artefact swamps the real signal.
Follow-up
- A handler is not idempotent and you have found 400 overlapping jobs. Which of them actually caused damage, and what would you query to find out?
- Peak concurrency for one job_type is 4 against a configured cap of 4. Is the cap working, or is the data hiding attempts that never started?
Track a rolling failure rate per destination for circuit decisions
The egress service delivers about 1,500 webhooks per second across roughly 40,000 destinations, each call bounded by a 10 second timeout. Maintain, per destination, the failure rate over the trailing 60 seconds so a caller can ask before dispatch whether the circuit should open. Attempts arrive as (destination_id, finished_at_ms, outcome). Requirement: amortised O(1) per attempt, with total memory bounded by the destination count rather than by traffic. Give the structure, its exact memory, and the rule that stops a destination with three attempts from opening a circuit.
Approach
- Name the exact-deque version and then reject it as the default. Holding timestamps and advancing a tail pointer past anything older than now minus 60 seconds is a correct two-pointer window at amortised O(1) per attempt, but its memory tracks in-window traffic, so one destination in a retry storm holds hundreds of thousands of entries while thousands of quiet destinations hold none.
- Use a ring of 60 one-second buckets per destination, each bucket a pair of counters for attempts and failures. On an attempt, advance the ring by the elapsed whole seconds, zeroing at most min(elapsed, 60) buckets, then increment the head. That is amortised O(1) with a fixed footprint per destination.
- State the footprint: 60 buckets times two 4-byte counters is 480 bytes of payload per destination, so 40,000 destinations is roughly 20 to 25 MB with per-entry overhead, bounded by the catalogue rather than by the rate. The cost is granularity, since the oldest bucket ages out in whole seconds, which is far tighter than the decision needs.
- Require a minimum sample before the circuit may open. A destination with three attempts and three failures reads as 100 percent and is not evidence; a floor of roughly 20 attempts in the window makes the ratio meaningful, and below that floor use a run of consecutive failures as the trigger instead.
Follow-up
- The fleet is 30 instances and each sees roughly a thirtieth of a destination's traffic. Where does the rate actually live, and what does a per-instance answer get wrong?
- A destination answers in 9.5 seconds and succeeds. It is not failing but it is consuming your per-destination concurrency. What signal should open the circuit here?
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?
Discuss the trade-offs between SQL and NoSQL databases for a data-intensive application.
Discuss the trade-offs between SQL and NoSQL databases for a data-intensive application.
Approach
- Name the grain you start from and join outward from it.
- Check whether any join is one-to-many before aggregating, or the sums inflate.
- Say which index the query would use, and what makes it unusable.
- 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?
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 differences between monolithic and microservices architectures in the context of high-traffic
Explain the core differences between monolithic and microservices architectures in the context of 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?
How do you approach optimizing database queries for applications with significant latency requirements?
How do you approach optimizing database queries for applications with significant latency requirements?
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 primary security considerations you prioritize when designing an API?
What are the primary security considerations you prioritize when designing an API?
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 stay current with evolving frameworks, and how do you decide when to adopt a new technology for a p
How do you stay current with evolving frameworks, and how do you decide when to adopt a new technology for a production project?
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 system to handle a sudden, massive spike in concurrent user traffic?
How would you design a system to handle a sudden, massive spike in concurrent user traffic?
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 strategies do you employ to ensure high availability and disaster recovery in cloud-native environments?
What strategies do you employ to ensure high availability and disaster recovery in cloud-native environments?
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 do you manage state in a distributed system?
How do you manage state in a distributed system?
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 situation where you had to provide constructive feedback to a peer regarding their code or architec
Describe a situation where you had to provide constructive feedback to a peer regarding their code or architectural design.
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 scenario where you had to debug a production issue in a complex environment; what was your systemat
Describe a scenario where you had to debug a production issue in a complex environment; what was your systematic process?
Approach
- Establish what changed and when, before forming any theory.
- Pick a bisection that eliminates candidates whichever way it turns out.
- Check the instrumentation before believing the symptom.
- Separate the trigger from the cause; the deploy is rarely the bug.
Follow-up
- What would you look at first, and what would it rule out?
- How would you tell a cause from a coincidence here?
Built from the rounds and topics Sundew candidates report.
Prepare, practise & reflect
One practical outcome each day. Spend longer where you need it.
0 / 7 done01Map the Sundew loop
- Write out the reported sequence: Technical Background Screening, Deep-Dive Technical Assessments, Team-Fit Discussions.
- 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 MEAN Stack
- Spend the session on MEAN Stack, which Sundew candidates report being tested on.
- Write one worked example in MEAN Stack and time yourself on it.
Deliverable: One timed worked example in MEAN Stack.
03Work MERN Stack
- Spend the session on MERN Stack, which Sundew candidates report being tested on.
- Write one worked example in MERN Stack and time yourself on it.
Deliverable: One timed worked example in MERN Stack.
04Work Full-Stack Development
- Spend the session on Full-Stack Development, which Sundew candidates report being tested on.
- Write one worked example in Full-Stack Development and time yourself on it.
Deliverable: One timed worked example in Full-Stack Development.
05Answer out loud: Technical Domain Expertise
- Answer aloud, timed: Explain the core differences between monolithic and microservices architectures in the context of high-traffic applications.
- Answer aloud, timed: How do you approach optimizing database queries for applications with significant latency requirements?
Deliverable: Spoken answers to 2 reported Technical Domain Expertise question(s), under time.
06Answer out loud: System Design and Scalability
- Answer aloud, timed: How would you design a system to handle a sudden, massive spike in concurrent user traffic?
- Answer aloud, timed: What strategies do you employ to ensure high availability and disaster recovery in cloud-native environments?
Deliverable: Spoken answers to 2 reported System Design and Scalability question(s), under time.
07Answer out loud: Behavioral and Problem-Solving
- Answer aloud, timed: Tell me about a time you had to pivot your technical approach due to changing business requirements.
- Answer aloud, timed: How do you handle technical debt while balancing the need for rapid feature delivery?
Deliverable: Spoken answers to 2 reported Behavioral and Problem-Solving 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.
Tell me about a time you had to pivot your technical approach due to changing business requirements.
Tell me about a time you had to pivot your technical approach due to changing business requirements.
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 technical debt while balancing the need for rapid feature delivery?
How do you handle technical debt while balancing the need for rapid feature delivery?
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 is your process for breaking down a complex, ill-defined project into actionable technical tasks?
What is your process for breaking down a complex, ill-defined project into actionable technical tasks?
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
Tell me about a time you had to pivot your technical approach due to changing business requirements.
- 02
How do you handle technical debt while balancing the need for rapid feature delivery?
- 03
What is your process for breaking down a complex, ill-defined project into actionable technical tasks?
How long should I spend preparing for the technical rounds?
We recommend focusing on your core domain expertise and reviewing architectural trade-offs; for most candidates, this requires 2–4 weeks of focused study.
Sundew Software Engineer candidate reports ↗Is the technical assessment based on a live coding environment?
Yes, expect a mix of collaborative coding sessions and architectural discussions where you will be asked to solve problems in real-time.
Sundew Software Engineer candidate reports ↗What is the culture at Sundew like for engineers?
We foster a culture of technical excellence, continuous learning, and collaborative problem-solving, where engineers are encouraged to take ownership of their work.
Sundew Software Engineer candidate reports ↗How soon can I expect a decision after the final round?
We aim to provide feedback as quickly as possible, typically within a few business days following your final interview.
Sundew Software Engineer candidate reports ↗What topics does Sundew test in interviews?
Sundew interviews most often cover Version Control (Git), Performance Optimization, MongoDB, Scalability, and Automation Scripting. The exact emphasis depends on the specific role you apply for.
Sundew 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.
- 01Sundew 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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