Interview guides · Hazen and Sawyer

Hazen and Sawyer Software Engineer Interview Guide

Hazen and Sawyer Software Engineer interview guide: reported rounds, questions and how candidates describe the process.

The 60-second brief

At Hazen and Sawyer, a Software Engineer occupies a unique position at the intersection of technical computing, environmental data, and civil infrastructure modeling. Unlike traditional pure-tech environments, software engineering at Hazen and Sawyer directly supports the firm’s core mission: delivering clean water solutions, protecting public health, and optimizing complex water resource management systems. You will build, customize, and maintain digital tools, simulation frameworks, data pipelines, and internal platforms used by hydrogeologists, structural engineers, and water resource specialists across the firm. Your work directly impacts how project teams visualize environmental data, run predictive water quality models, and automate complex engineering calculations.

This guide is scoped to a Software Engineer candidate at Hazen and Sawyer.

Focus areas

Behavioral interview questions
Communication skills
Culture fit / professionalism

The Hazen and Sawyer interview process

Hazen and Sawyer candidates report 4 rounds over 3-5 weeks. The stages below are what candidates describe, not a published process.

Initial Screening

Conducted via video call or at a university career fair, focusing on background, resume highlights, and career interests.

What to demonstrate

Conducted via video call or at a university career fair
Focusing on background, resume highlights, and career interests

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.

Secondary Interview Stage

Involves a series of 1 on 1 or panel conversations, either virtually or on-site, lasting two to four hours.

What to demonstrate

Involves a series of 1 on 1 or panel conversations, either virtually or on-site, lasting two to four hours
Depth in Behavioral interview questions

How to prepare

Answer aloud and timed: How has your academic background or prior experience prepared you to solve problems in an environmental and civil engineering environment?
Answer aloud and timed: Explain a complex technical mechanism or project component from your previous experience as if you were explaining it to a non-technical project manager.

Team Interaction

Candidates discuss real-world projects and evaluate alignment with the team's working style.

What to demonstrate

Candidates discuss real-world projects and evaluate alignment with the team's working style
Depth in Behavioral interview questions

How to prepare

Answer aloud and timed: What specific tools, languages, or software frameworks did you rely on in your most significant project, and why were they chosen?
Answer aloud and timed: What draws you to Hazen and Sawyer's mission in the water and environmental engineering space?

Final Offer Discussions

Candidates engage in discussions regarding the final offer after the interview rounds.

What to demonstrate

Candidates engage in discussions regarding the final offer after the interview rounds
Depth in Behavioral interview questions

How to prepare

Answer aloud and timed: Tell me about a time you had to work closely with professionals from disciplines outside your primary field of expertise.
Answer aloud and timed: How do you prioritize your tasks when managing competing demands across multiple project stakeholders?

Where candidates lose points

Prepare detailed stories from your resume

Be ready to walk through your key projects line by line. Clearly explain your personal contribution, the technology stack chosen, technical challenges overcome, and final outcomes.

Emphasize clarity over technical buzzwords

When answering technical questions, focus on clear, logical explanations. Interviewers value candidates who can explain complex computational concepts plainly to cross-functional team members.

Prepare thoughtful questions for every interviewer

Because you will meet with multiple individuals across 30-minute sessions or panels, tailor your questions to each person’s role. Ask project managers about team structure and discipline leads about future technology adoption.

Follow-up communication between interview stages can sometimes experience delays due to busy project schedules

Maintain proactive, polite email communication with your primary point of contact to stay informed.

Questions & practice

Identify the heaviest tenants in a five-minute window under memory pressure

Medium · top-k · heavy hitters · streaming

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?

Diff a projection against the primary without per-row point reads

Hard · reconciliation · range hashing · throttling

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?

Track a rolling failure rate per destination for circuit decisions

Easy · sliding window · ring buffer · circuit breaker

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?

Keep soft-deleted accounts from blocking re-registration

Easy · soft delete · unique constraints · engine differences

app_user holds user_id, tenant_id, email CITEXT, password_hash (NULL for SSO principals), email_verified_at, auth_version, status ('invited','active','suspended','deactivated'), created_at, updated_at, deleted_at. Two live accounts for one address inside a tenant must be impossible, but an address freed by a soft delete must be reusable, and the same tenant may delete and re-register it repeatedly. Write the uniqueness DDL for PostgreSQL 16, then the equivalent for MySQL 8 where partial indexes do not exist, and say what each permits once three deleted rows already hold that address.

Approach

Start from what is actually unique: not (tenant_id, email), but (tenant_id, email) among live rows. PostgreSQL says that directly — CREATE UNIQUE INDEX app_user_live_email ON app_user (tenant_id, email) WHERE deleted_at IS NULL. A full constraint over the same two columns burns the address permanently the first time someone deletes an account.
Keep case-insensitivity in the type or the index, never in the application: CITEXT as given, or UNIQUE (tenant_id, lower(email)) as an expression index where the extension is unavailable. A case-sensitive unique column is exactly how two accounts for one human appear.
For MySQL 8 the predicate has to move inside the key: add a discriminator column that is a constant 0 while the row is live and is set to user_id on delete, with UNIQUE (tenant_id, email, deleted_marker). Live rows share the constant and still collide; deleted rows differ from each other and stop colliding.
State the NULL variant and its dependency: leaving the marker NULL for deleted rows also works, because a unique index treats NULLs as distinct — true in MySQL, and true in PostgreSQL only under the default NULLS DISTINCT, which PostgreSQL 15 lets you reverse. Check the polarity against the three existing deleted rows: constant-on-live is what preserves the collision you want, and reversing it silently admits duplicate live accounts.

Follow-up

A deleted account re-registers with the same address the next day. Do the old resource rows follow the new user_id, and how does the API keep the two principals apart?
How do you honour an erasure request while resource_revision.actor_user_id still references this table?

Denormalise tenant onto revisions and backfill it live

Hard · denormalisation · online migration · backfill

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?

Can you walk us through a key technical project on your resume and detail your specific role in its execution?

Medium · Resume & Academic Project Deep Dives

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 challenging engineering or computational problem you encountered in a recent project and how you re

Medium · Resume & Academic Project Deep Dives

Describe a challenging engineering or computational problem you encountered in a recent project and how you resolved 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?

How has your academic background or prior experience prepared you to solve problems in an environmental and ci

Medium · Resume & Academic Project Deep Dives

How has your academic background or prior experience prepared you to solve problems in an environmental and civil engineering 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?

Explain a complex technical mechanism or project component from your previous experience as if you were explai

Medium · Resume & Academic Project Deep Dives

Explain a complex technical mechanism or project component from your previous experience as if you were explaining it to a non-technical project manager.

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 specific tools, languages, or software frameworks did you rely on in your most significant project, and w

Medium · Resume & Academic Project Deep Dives

What specific tools, languages, or software frameworks did you rely on in your most significant project, and why were they chosen?

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 approach structuring data and software workflows when working with large or unstructured environmen

Medium · Technical Approach & Practical Problem-S

How do you approach structuring data and software workflows when working with large or unstructured environmental datasets?

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?

If asked to support a project team in a domain you are unfamiliar with, how would you go about bringing yourse

Medium · Technical Approach & Practical Problem-S

If asked to support a project team in a domain you are unfamiliar with, how would you go about bringing yourself up to speed?

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 process for ensuring quality control and accuracy in your code or analytical models.

Medium · Technical Approach & Practical Problem-S

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 evaluate whether an existing tool should be customized versus building a custom solution from scrat

Medium · Technical Approach & Practical Problem-S

How do you evaluate whether an existing tool should be customized versus building a custom solution from scratch?

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?

Read latency spikes on a sixty-second sawtooth

Medium · cache stampede · single-flight · ttl

The cached listing read path serves about 14k reads/second at an 85% hit rate. p99 sits at 35 ms for 57 seconds, jumps to 900 ms for 3, and repeats. During each spike the primary shows several hundred identical listing queries starting within the same millisecond, all carrying one large tenant's id. Cache entries use a 60-second TTL. Give the mechanism, the ordered checks, the fix, and the correctness hazard your fix must not introduce.

Approach

Match the period to a configured number before theorising about load. A spike every 60 seconds against a 60-second TTL is an entry expiring, and you confirm it by correlating spike timestamps with the entry's write time rather than with the traffic curve. If the period had matched a cron or a GC interval instead, this is a different investigation.
Establish the concurrency of the miss. Several hundred identical queries in one millisecond means the miss path has no coalescing: every request that arrives between expiry and repopulation recomputes. The herd size is that key's arrival rate times its recompute time, so at 1.2k reads/second for the hot key and a 250 ms recompute you expect about 300 concurrent misses, which matches what is observed.
Add single-flight on the miss path so one caller per key recomputes under a short-lived lock while the rest wait for its result. Prefer stale-while-revalidate where the read tolerates it: return the expired value immediately and refresh asynchronously, which removes the latency spike rather than serialising it into a queue of waiters.
De-synchronise the keys. Write TTLs with jitter, for example 60 seconds plus or minus 10%, so a deploy or a mass invalidation does not align every key on the same second and turn a per-key herd into a fleet-wide one.

Follow-up

The same sawtooth appears on a key that is invalidated on write rather than expired. Is that the same bug?
How does your answer change if the recompute takes 4 seconds instead of 250 ms?

Suggested practice checklist

Built from the rounds and topics Hazen and Sawyer candidates report.

Day 1 — Map the Hazen and Sawyer loop

Write out the reported sequence: Initial Screening, Secondary Interview Stage, Team Interaction, Final Offer 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 4 reported rounds, with the weakest marked.

Day 2 — Work Behavioral interview questions

Spend the session on Behavioral interview questions, which Hazen and Sawyer candidates report being tested on.
Write one worked example in Behavioral interview questions and time yourself on it.

Deliverable: One timed worked example in Behavioral interview questions.

Day 3 — Work Communication skills

Spend the session on Communication skills, which Hazen and Sawyer candidates report being tested on.
Write one worked example in Communication skills and time yourself on it.

Deliverable: One timed worked example in Communication skills.

Day 4 — Work Culture fit / professionalism

Spend the session on Culture fit / professionalism, which Hazen and Sawyer candidates report being tested on.
Write one worked example in Culture fit / professionalism and time yourself on it.

Deliverable: One timed worked example in Culture fit / professionalism.

Day 5 — Answer out loud: Resume & Academic Project Deep Dives

Answer aloud, timed: Can you walk us through a key technical project on your resume and detail your specific role in its execution?
Answer aloud, timed: Describe a challenging engineering or computational problem you encountered in a recent project and how you resolved it.

Deliverable: Spoken answers to 2 reported Resume & Academic Project Deep Dives question(s), under time.

Day 6 — Answer out loud: Behavioral & Culture Fit

Answer aloud, timed: What draws you to Hazen and Sawyer's mission in the water and environmental engineering space?
Answer aloud, timed: Tell me about a time you had to work closely with professionals from disciplines outside your primary field of expertise.

Deliverable: Spoken answers to 2 reported Behavioral & Culture Fit question(s), under time.

Day 7 — Answer out loud: Technical Approach & Practical Problem-Solving

Answer aloud, timed: How do you approach structuring data and software workflows when working with large or unstructured environmental datasets?
Answer aloud, timed: If asked to support a project team in a domain you are unfamiliar with, how would you go about bringing yourself up to speed?

Deliverable: Spoken answers to 2 reported Technical Approach & Practical Problem-Solving question(s), under time.

Behavioural preparation

Behavioural rounds judge the decision you made and what it cost.

What draws you to Hazen and Sawyer's mission in the water and environmental engineering space?

Medium · Behavioral & Culture Fit

Approach

Pick a story where you made the decision, not one where you watched it.
State the situation in two sentences and spend the rest on the reasoning.
Give the blast radius: what could have broken, and what you measured.
Name the disagreement and how you resolved it with evidence.

Follow-up

What would you do differently if you ran that again?
How did you know your change caused the improvement?

Tell me about a time you had to work closely with professionals from disciplines outside your primary field of

Medium · Behavioral & Culture Fit

Tell me about a time you had to work closely with professionals from disciplines outside your primary field of expertise.

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 prioritize your tasks when managing competing demands across multiple project stakeholders?

Medium · Behavioral & Culture Fit

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 received feedback or faced a project delay. How did you adapt your approach?

Medium · Behavioral & Culture Fit

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?

Where do you see your career evolving over the next few years, and what skills are you looking to develop here

Medium · Behavioral & Culture Fit

Where do you see your career evolving over the next few years, and what skills are you looking to develop here?

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 changing requirements or vague specifications from internal clients or project managers?

Medium · Technical Approach & Practical Problem-S

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?