At SCS Consulting Group, the Software Engineer role serves as a critical bridge between advanced civil engineering principles and the digital tools required to manage complex infrastructure projects. You will be responsible for developing, maintaining, and optimizing the software solutions that drive our Stormwater Management and Cost Sharing initiatives. Your work directly impacts how our teams analyze environmental data, model hydrological systems, and ensure equitable cost distribution across municipal projects. This role is not merely about writing code; it is about solving tangible, real-world engineering challenges that affect urban development and environmental sustainability. You will collaborate closely with Intermediate Civil Engineers and project managers to translate complex regulatory and technical requirements into robust, scalable software applications. By joining SCS Consulting Group, you are positioning yourself at the intersection of civil infrastructure and technical innovation, where your contributions will directly influence the efficiency and accuracy of our firm’s most critical consulting services.
Technical Screening
reportedInitial evaluation of your technical skills and knowledge.
What to demonstrate
- Initial evaluation of your technical skills and knowledge
- Depth in Software Engineering (General)
How to prepare
- Answer aloud and timed: How would you design a software solution to handle large-scale hydrological datasets?
- Answer aloud and timed: Describe your experience integrating custom software tools with existing civil engineering modeling software.
Problem-Solving Discussion
reportedDeeper dive into your problem-solving methodology and approach.
What to demonstrate
- Deeper dive into your problem-solving methodology and approach
- Depth in Software Engineering (General)
How to prepare
- Answer aloud and timed: How do you ensure data integrity when performing complex cost-sharing calculations?
- Answer aloud and timed: Explain a time you had to troubleshoot a performance bottleneck in a data-heavy application.
Behavioral Interview
reportedFocus on your past professional experiences and cultural fit.
What to demonstrate
- Focus on your past professional experiences and cultural fit
- Depth in Software Engineering (General)
How to prepare
- Prepare three examples from your own work, each with a decision you made and an outcome you can quantify.
- Re-read the description of the behavioral interview above and write down what you would ask to confirm before it.
Technical Case Studies
reportedEngagement in technical case studies relevant to the industry.
What to demonstrate
- Engagement in technical case studies relevant to the industry
- Depth in Software Engineering (General)
How to prepare
- Answer aloud and timed: How do you prioritize features when faced with tight project deadlines and changing regulatory requirements?
- Answer aloud and timed: Describe a situation where you identified a flaw in a project’s technical approach and how you addressed it.
Whiteboarding Sessions
reportedCollaborative sessions to demonstrate your thought process and solutions.
What to demonstrate
- Collaborative sessions to demonstrate your thought process and solutions
- Depth in Software Engineering (General)
How to prepare
- Answer aloud and timed: How do you handle situations where the project scope expands significantly during the development phase?
- Answer aloud and timed: Tell us about a time you had to explain a complex technical issue to a civil engineer or project manager.
Final Discussions
reportedConcluding conversations with team members to assess overall fit.
What to demonstrate
- Concluding conversations with team members to assess overall fit
- Depth in Software Engineering (General)
How to prepare
- Answer aloud and timed: Describe your experience working in an environment where engineering standards and software requirements must align.
- Answer aloud and timed: How do you handle feedback on your code or design architecture from team members?
PracHub editorial advice for the preparation topics above.
Understand our projects
Research the types of Stormwater Management and Cost Sharing projects SCS Consulting Group handles. Knowing our focus areas will help you tailor your answers.
Structure your answers
Use the STAR method (Situation, Task, Action, Result) for behavioral questions to ensure your responses are concise and impactful.
Ask thoughtful questions
At the end of your interviews, ask about the team's current technical challenges or how the software department supports the firm's long-term goals.
Be prepared for ambiguity
In consulting, requirements can evolve. Show that you are comfortable working in environments where you might need to clarify project goals as you go.
Choose a category, try a prompt, then open its approach, worked solution or follow-up when you need it.
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?
Diff a projection against the primary without per-row point reads
The listing projection has drifted and some rows show a stale version. The primary holds 40,000,000 resource rows across 12,000 tenants while serving 1,200 writes and 14,000 reads per second. The obvious repair, reading each resource row and comparing its version against the projection, is correct and would eventually finish. Explain precisely why it is unacceptable here, then give a diff that finds the differing rows, state its complexity, and make it safe to run against a live primary. Replication lag is usually under 100 ms and is not bounded.
Approach
- Quantify the naive cost rather than calling it slow: 40,000,000 point reads at even 0.5 ms each is over five hours serialised, and the only lever is concurrency, which is exactly what you cannot spend. The primary's pool is sized for the write path, and 40,000,000 random reads evict the buffer cache that sustains the 85 percent cache hit rate, so the audit degrades the system it is auditing.
- Replace random access with one ordered pass per side. Both sides can be read in (tenant_id, resource_id) order, which is a sequential scan on each and a merge join in O(n) time and O(1) memory. For a dense diff that is the whole answer, and it reads the primary once instead of 40,000,000 times.
- For the expected sparse case, compare range hashes instead of rows: partition the key space, compute per range an order-independent aggregate over hash(resource_id, version), compare aggregates, and descend only into ranges that differ. With d differing rows and branching factor B, at most d ranges mismatch per level, so the drill-down examines O(d log_B(n/d)) ranges and reads full rows only in mismatching leaves.
- Aggregate with a sum modulo 2^64 or a multiset hash, never XOR. XOR is order-independent but self-cancelling, so two rows wrong in the same way, or a row duplicated on one side, leave the range aggregate matching and the range is declared clean.
Follow-up
- The diff reports 900 stale rows. How do you decide between patching those rows and rebuilding the projection from resource_revision?
- Same job, but the projection lives in a search index that cannot be scanned in key order. What changes?
Canonicalise a request body into a stable idempotency fingerprint
idempotency_key.request_fingerprint is a SHA-256 over the method, path and canonicalised body, and a retry whose fingerprint differs must be rejected with 422 rather than served the stored response. Write the canonicaliser. Bodies are JSON up to 256 KB nested at most 32 levels; clients vary key order, whitespace and unicode escaping, and some send 64-bit ids as JSON numbers. Produce a deterministic byte string such that semantically identical bodies match and any semantic difference does not. State your complexity and name two normalisations you refuse to perform.
Approach
- Parse once into a tree, then re-serialise under fixed rules: object keys sorted, array order preserved, one escaping convention, no insignificant whitespace. Parsing is O(n) and sorting keys is O(k log k) per object, so O(n log n) overall with O(depth) stack, and the 32-level cap is enforced during parsing because hostile nesting is how a canonicaliser becomes a stack overflow.
- Sort keys by their UTF-8 bytes and say why the obvious implementation is wrong in some runtimes: a default string comparison that orders by UTF-16 code units places surrogate pairs, meaning code points from U+10000 up, below U+E000 to U+FFFF, which is not UTF-8 byte order, so two services written in different languages disagree on the same document.
- Do not re-encode numbers through a double. IEEE-754 binary64 represents integers exactly only up to 2^53, so normalising a 19-digit id through a float changes it, and 1 against 1.0 cannot be reconciled without deciding whether they are the same value. Preserve the literal token, and require ids as strings at the API boundary if you want them comparable.
- Reject duplicate keys rather than picking one. JSON permits them and parsers disagree, most keeping the last, so any choice you make ties the fingerprint to a parser detail that the code handling the request does not necessarily share.
Follow-up
- A client sends the same logical request with an extra field your API ignores. Same key, different fingerprint, so you return 422. Is that the right answer?
- Where does the fingerprint get computed relative to request decompression and the body-size limit?
Denormalise tenant onto revisions and backfill it live
resource_revision (revision_id, resource_id, version, actor_user_id, change_kind, patch, request_id, created_at) has 400M rows and no tenant column; tenant_id lives only on resource. Two reads need it: a tenant-scoped audit feed ordered by created_at DESC, and an offboarding purge. Both join back to resource today. Justify adding tenant_id to resource_revision against those two reads, name the anomaly the copy introduces and the constraint that prevents it, then give the ordered migration for a live table taking 1.2k writes/second — the lock each step takes, how the backfill is batched, and where each step stops being reversible. PostgreSQL 16.
Approach
- Justify from the access path rather than from taste. Without the column, the audit feed either scans resource_revision by created_at and discards other tenants' rows, or resolves the tenant's resource_ids first and probes with them — both proportional to the tenant's whole history rather than to one page. With (tenant_id, created_at DESC, revision_id DESC) it is a seek that stops at 50 rows, and the purge becomes a ranged delete instead of a join.
- Name the cost exactly: a second copy of a fact can disagree with the first. Make the disagreement unwritable rather than documented — add UNIQUE (resource_id, tenant_id) on resource so it can serve as a foreign-key target, then FOREIGN KEY (resource_id, tenant_id) REFERENCES resource (resource_id, tenant_id) on the revision table. A revision can then only ever carry its parent's tenant.
- Step one, expand: ALTER TABLE resource_revision ADD COLUMN tenant_id BIGINT NULL, with no default, so it is a catalogue change and no rewrite. It still needs ACCESS EXCLUSIVE for an instant, and that instant queues behind the longest open transaction on the table while every later query queues behind it — set lock_timeout to 2s and retry rather than wait.
- Step two, dual-write: deploy the writer that populates tenant_id on every new revision while reads still use the join. Reversible by redeploying the previous build, because nothing reads the column yet.
Follow-up
- The backfill is half finished and a rollback is required. What state is the table in, and what does the previous build do with a half-populated column?
- How do you verify the backfill actually finished, given rows are still being inserted while it runs?
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?
How would you design a software solution to handle large-scale hydrological datasets?
How would you design a software solution to handle large-scale hydrological datasets?
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 ensure data integrity when performing complex cost-sharing calculations?
How do you ensure data integrity when performing complex cost-sharing calculations?
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 strategies do you use to maintain legacy code while introducing new features?
What strategies do you use to maintain legacy code while introducing new features?
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?
Walk us through your process for gathering requirements from non-technical stakeholders.
Walk us through your process for gathering requirements from non-technical stakeholders.
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 do you prioritize features when faced with tight project deadlines and changing regulatory requirements?
How do you prioritize features when faced with tight project deadlines and changing regulatory 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?
Describe a situation where you identified a flaw in a project’s technical approach and how you addressed it.
Describe a situation where you identified a flaw in a project’s technical approach and how you addressed it.
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 a time you had to troubleshoot a performance bottleneck in a data-heavy application.
Explain a time you had to troubleshoot a performance bottleneck in a data-heavy application.
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 SCS Consulting Group candidates report.
Prepare, practise & reflect
One practical outcome each day. Spend longer where you need it.
0 / 7 done01Map the SCS Consulting Group loop
- Write out the reported sequence: Technical Screening, Problem-Solving Discussion, Behavioral Interview, Technical Case Studies, Whiteboarding Sessions, Final 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 6 reported rounds, with the weakest marked.
02Work Software Engineering (General)
- Spend the session on Software Engineering (General), which SCS Consulting Group candidates report being tested on.
- Write one worked example in Software Engineering (General) and time yourself on it.
Deliverable: One timed worked example in Software Engineering (General).
03Work Programming Fundamentals
- Spend the session on Programming Fundamentals, which SCS Consulting Group candidates report being tested on.
- Write one worked example in Programming Fundamentals and time yourself on it.
Deliverable: One timed worked example in Programming Fundamentals.
04Work Problem Solving
- Spend the session on Problem Solving, which SCS Consulting Group candidates report being tested on.
- Write one worked example in Problem Solving and time yourself on it.
Deliverable: One timed worked example in Problem Solving.
05Answer out loud: Technical and Domain Expertise
- Answer aloud, timed: How would you design a software solution to handle large-scale hydrological datasets?
- Answer aloud, timed: Describe your experience integrating custom software tools with existing civil engineering modeling software.
Deliverable: Spoken answers to 2 reported Technical and Domain Expertise question(s), under time.
06Answer out loud: Problem-Solving and Methodology
- Answer aloud, timed: Walk us through your process for gathering requirements from non-technical stakeholders.
- Answer aloud, timed: How do you prioritize features when faced with tight project deadlines and changing regulatory requirements?
Deliverable: Spoken answers to 2 reported Problem-Solving and Methodology question(s), under time.
07Answer out loud: Behavioral and Collaboration
- Answer aloud, timed: Tell us about a time you had to explain a complex technical issue to a civil engineer or project manager.
- Answer aloud, timed: Describe your experience working in an environment where engineering standards and software requirements must align.
Deliverable: Spoken answers to 2 reported Behavioral and Collaboration 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.
Describe your experience integrating custom software tools with existing civil engineering modeling software.
Describe your experience integrating custom software tools with existing civil engineering modeling software.
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 the project scope expands significantly during the development phase?
How do you handle situations where the project scope expands significantly during the development phase?
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 explain a complex technical issue to a civil engineer or project manager.
Tell us about a time you had to explain a complex technical issue to a civil engineer or project manager.
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 your experience working in an environment where engineering standards and software requirements must
Describe your experience working in an environment where engineering standards and software requirements must align.
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 on your code or design architecture from team members?
How do you handle feedback on your code or design architecture from team members?
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
Describe your experience integrating custom software tools with existing civil engineering modeling software.
- 02
How do you handle situations where the project scope expands significantly during the development phase?
- 03
Tell us about a time you had to explain a complex technical issue to a civil engineer or project manager.
- 04
Describe your experience working in an environment where engineering standards and software requirements must align.
How difficult are the technical assessments?
The assessments are practical rather than purely theoretical. They are designed to test your ability to solve problems you would actually encounter in our daily operations, rather than checking for memorization of niche algorithms.
SCS Consulting Group Software Engineer candidate reports ↗What is the typical timeline for the hiring process?
From the initial screening to a final decision, the process usually spans 3 to 6 weeks. We aim to move efficiently while ensuring you have enough time to meet with the relevant project leads.
SCS Consulting Group Software Engineer candidate reports ↗Is remote work an option for this position?
While we offer some flexibility, this role requires close collaboration with engineering teams, often necessitating a presence in the Markham or Toronto offices to facilitate effective teamwork and project alignment.
SCS Consulting Group Software Engineer candidate reports ↗What differentiates a successful candidate from others?
The most successful candidates are those who show genuine curiosity about the civil engineering problems we solve. Those who can demonstrate how their software engineering skills directly provide value to our clients stand out significantly.
SCS Consulting Group Software Engineer candidate reports ↗What topics does SCS Consulting Group test in interviews?
SCS Consulting Group interviews most often cover Software Engineering (General), Programming Fundamentals, Problem Solving, Version Control (Git), and Data Structures & Algorithms. The exact emphasis depends on the specific role you apply for.
SCS Consulting Group 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.
- 01SCS Consulting Group 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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