A Software Engineer at Waste Connections plays a critical role in designing, developing, and maintaining the digital infrastructure that powers one of the largest waste management and environmental services companies in North America. Unlike typical software companies where code remains entirely virtual, the technology you build here has a direct, tangible impact on physical operations. From route optimization algorithms for waste collection fleets to complex landfill management systems, customer portals, and billing engines, your work keeps essential services running smoothly across hundreds of communities. At Waste Connections, the software engineering team focuses on solving complex logistical and operational challenges. You will work on integrating legacy systems with modern cloud architectures, optimizing large-scale SQL databases, and building robust APIs. The problems you solve require a practical, hands-on mindset, as our software directly interacts with dispatchers, drivers, landfill operators, and municipal partners. This role is ideal for engineers who thrive on creating highly reliable, efficient, and scalable software that addresses real-world operational bottlenecks. You will collaborate closely with cross-functional teams, regional managers, and fellow developers to ensure that our technology stack supports the company's decentralized operating model and commitment to safety, integrity, and customer service.
Recruiter Screen
reportedInitial discussion with a recruiter about your background and interest in the company.
What to demonstrate
- Initial discussion with a recruiter about your background and interest in the company
- Depth in SQL
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 Assessment
reportedIncludes a written SQL test or general software engineering questionnaire to verify technical knowledge.
What to demonstrate
- Includes a written SQL test or general software engineering questionnaire to verify technical knowledge
- Depth in SQL
How to prepare
- Answer aloud and timed: How do you optimize a slow-running database query, and what role do indexes play in this process?
- Answer aloud and timed: Describe your experience with object-oriented programming (OOP) principles and how you apply them to build maintainable codebase structures.
Final Interview Rounds
reportedDeep-dive conversations with hiring managers, lead engineers, and potential team members.
What to demonstrate
- Deep-dive conversations with hiring managers, lead engineers, and potential team members
- Depth in SQL
How to prepare
- Answer aloud and timed: Walk me through the lifecycle of a software development project you completed, focusing on how you gathered requirements and tested your code.
- Answer aloud and timed: Tell me about a time when you had to work with a difficult team member or classmate. How did you handle the situation to ensure the project was successful?
PracHub editorial advice for the preparation topics above.
Brush up on your SQL
Database engineering is a core part of our tech stack. Spend time practicing joins, aggregations, subqueries, and indexing concepts before your technical assessment.
Emphasize practical solutions
During technical discussions, focus on building reliable, maintainable systems. Avoid over-engineering or proposing overly complex architectures when a simple, robust solution will solve the problem.
Be ready for landfill-related context
We are an environmental services and waste management company. Showing respect for, and interest in, the physical operations of our business—including landfills and recycling facilities—is highly valued by our hiring managers.
Choose a category, try a prompt, then open its approach, worked solution or follow-up when you need it.
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?
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?
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?
Write a SQL query to join multiple tables, filter records based on specific operational dates, and aggregate t
Write a SQL query to join multiple tables, filter records based on specific operational dates, and aggregate the results.
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?
Explain the difference between an inner join, a left join, and a outer join, and describe a scenario where you
Explain the difference between an inner join, a left join, and a outer join, and describe a scenario where you would use each.
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?
How do you optimize a slow-running database query, and what role do indexes play in this process?
How do you optimize a slow-running database query, and what role do indexes play in this process?
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?
Walk me through the lifecycle of a software development project you completed, focusing on how you gathered re
Walk me through the lifecycle of a software development project you completed, focusing on how you gathered requirements and tested your code.
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 feel about developing software that directly impacts physical, industrial, and landfill operations?
How do you feel about developing software that directly impacts physical, industrial, and landfill operations?
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 how you would approach gathering software requirements from non-technical stakeholders, such as regio
Describe how you would approach gathering software requirements from non-technical stakeholders, such as regional operations managers or dispatchers.
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?
Every query on one table stalls for forty seconds mid-deploy
During a release on PostgreSQL, every query touching resource times out for about 40 seconds and then recovers with no intervention. The release ran one migration, ALTER TABLE resource ADD COLUMN archived_reason TEXT, and the migration log shows it completing in 6 ms. Unrelated tables showed no change in error rate. Explain how a 6 ms statement caused a 40-second stall, give the ordered checks you would run on a live system to confirm it, and give the migration procedure that prevents a repeat.
Approach
- Separate the statement's duration from the lock's duration. ADD COLUMN with no default is a catalogue-only change and genuinely runs in milliseconds, but it requires ACCESS EXCLUSIVE, and it cannot acquire that until every transaction already touching the table has finished.
- Account for the queueing, which is the part that surprises people. A lock request that is waiting blocks later requests for conflicting modes behind it rather than letting them overtake, so one long-open transaction holds the DDL and the DDL holds all the traffic. The stall length is set by the longest open transaction, not by the size of the change.
- Confirm on a live system in this order: pg_stat_activity for that table ordered by xact_start, looking for the oldest transaction and specifically for state = idle in transaction; then pg_locks where granted = false to find the waiter; then join them on pid to name blocker and blocked. pg_blocking_pids() does that join for you and is the fastest single call.
- Prevent rather than merely time it better. Set lock_timeout to a second or two on the migration session so the DDL abandons the queue after a bounded wait and is retried, instead of holding it for as long as the oldest transaction lives. Be exact about what that buys: queries arriving during the wait still queue behind the pending ACCESS EXCLUSIVE request, so each attempt costs them up to one lock_timeout of added latency. The outage goes from 40 seconds to about one second per attempt, not to zero. Also run migrations away from deploy-time peaks, and put a statement timeout and an idle-in-transaction timeout on the analytics role that opens the long transactions.
Follow-up
- The same release also wants NOT NULL on that column. What is the sequence that gets there without a long lock?
- Your lock_timeout retry fails ten times in a row because the analytics transaction is always open. What do you change?
Built from the rounds and topics Waste Connections candidates report.
Prepare, practise & reflect
One practical outcome each day. Spend longer where you need it.
0 / 7 done01Map the Waste Connections loop
- Write out the reported sequence: Recruiter Screen, Technical Assessment, Final Interview Rounds.
- 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 SQL
- Spend the session on SQL, which Waste Connections candidates report being tested on.
- Write one worked example in SQL and time yourself on it.
Deliverable: One timed worked example in SQL.
03Work Behavioral Interviewing
- Spend the session on Behavioral Interviewing, which Waste Connections candidates report being tested on.
- Write one worked example in Behavioral Interviewing and time yourself on it.
Deliverable: One timed worked example in Behavioral Interviewing.
04Work High-Level Software Development Q&A
- Spend the session on High-Level Software Development Q&A, which Waste Connections candidates report being tested on.
- Write one worked example in High-Level Software Development Q&A and time yourself on it.
Deliverable: One timed worked example in High-Level Software Development Q&A.
05Answer out loud: Technical and Database Fundamentals
- Answer aloud, timed: Write a SQL query to join multiple tables, filter records based on specific operational dates, and aggregate the results.
- Answer aloud, timed: Explain the difference between an inner join, a left join, and a outer join, and describe a scenario where you would use each.
Deliverable: Spoken answers to 2 reported Technical and Database Fundamentals question(s), under time.
06Answer out loud: Behavioral and Situational Alignment
- Answer aloud, timed: Tell me about a time when you had to work with a difficult team member or classmate. How did you handle the situation to ensure the project was successful?
- Answer aloud, timed: Describe a situation where you had to quickly learn a new technology or domain knowledge to solve a problem.
Deliverable: Spoken answers to 2 reported Behavioral and Situational Alignment question(s), under time.
07Answer out loud: Operational Adaptability
- Answer aloud, timed: How do you feel about developing software that directly impacts physical, industrial, and landfill operations?
- Answer aloud, timed: Describe how you would approach gathering software requirements from non-technical stakeholders, such as regional operations managers or dispatchers.
Deliverable: Spoken answers to 2 reported Operational Adaptability 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 with object-oriented programming (OOP) principles and how you apply them to build mai
Describe your experience with object-oriented programming (OOP) principles and how you apply them to build maintainable codebase structures.
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 when you had to work with a difficult team member or classmate. How did you handle the si
Tell me about a time when you had to work with a difficult team member or classmate. How did you handle the situation to ensure the project was successful?
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 quickly learn a new technology or domain knowledge to solve a problem.
Describe a situation where you had to quickly learn a new technology or domain knowledge to solve a problem.
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 or criticism on your code during peer reviews?
How do you handle feedback or criticism on your code during peer reviews?
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?
Who is a role model to you—both a famous figure and someone you know personally—and what qualities do you emul
Who is a role model to you—both a famous figure and someone you know personally—and what qualities do you emulate from them?
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 would you describe your working style, and how do you think your previous peers or managers would describe
How would you describe your working style, and how do you think your previous peers or managers would describe your contributions to a team?
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 working in an environment with high autonomy where you are expected to self-manage your task
How do you handle working in an environment with high autonomy where you are expected to self-manage your tasks and project timelines?
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 with object-oriented programming (OOP) principles and how you apply them to build maintainable codebase structures.
- 02
Tell me about a time when you had to work with a difficult team member or classmate. How did you handle the situation to ensure the project was successful?
- 03
Describe a situation where you had to quickly learn a new technology or domain knowledge to solve a problem.
- 04
How do you handle feedback or criticism on your code during peer reviews?
How difficult is the technical assessment at Waste Connections?
The assessment is designed to test practical, real-world knowledge rather than highly abstract algorithmic puzzles. If you have a solid grasp of SQL, relational databases, and general software development principles, you should find the test highly manageable. It is focused on ensuring you can perform day-to-day engineering tasks.
Waste Connections Software Engineer candidate reports ↗What is the company culture like for Software Engineers?
Our culture is highly collaborative, down-to-earth, and performance-driven. We operate with a decentralized structure, which means our engineering teams have a high degree of autonomy and are expected to take ownership of their projects. We value practical results, mutual respect, and a strong work ethic.
Waste Connections Software Engineer candidate reports ↗Do Software Engineers have to visit landfills or operational facilities?
While your day-to-day work is primarily office-based or hybrid, our engineers are highly encouraged to visit our local hauling depots, recycling centers, and landfills. Understanding the physical environment and talking directly to the people using our software is key to building highly effective tools for our business.
Waste Connections Software Engineer candidate reports ↗How quickly does the interview process move?
We respect our candidates' time and aim to keep the process moving efficiently. Typically, the entire process—from the initial recruiter screen to a final decision—takes between two to four weeks, depending on candidate availability and scheduling.
Waste Connections Software Engineer candidate reports ↗What topics does Waste Connections test in interviews?
Waste Connections interviews most often cover Phone Interviewing, Sales experience (account executive/inside sales), Excel, SQL, and Familiarity with waste management. The exact emphasis depends on the specific role you apply for.
Waste Connections 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.
- 01Waste Connections 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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