Interview guides · Quest Medical

Quest Medical Software Engineer Interview Guide

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

The 60-second brief

A Software Engineer at Quest Medical plays a critical role in the development, testing, and maintenance of software systems that power advanced medical devices and manufacturing technologies. Unlike traditional software roles focused solely on web applications, engineering at Quest Medical is deeply integrated with physical products, cleanroom operations, and clinical environments. Your work directly impacts patient safety and product reliability, requiring a meticulous approach to software quality, systems integration, and regulatory compliance. In this position, you will contribute to a variety of internal and external software solutions. This includes embedded software for medical devices, automation tools for manufacturing and quality control, and diagnostic systems used by field service engineers.

This guide is scoped to a Software Engineer candidate at Quest Medical.

Focus areas

Cleanroom/sterilization processes
Medical device / disposables domain knowledge
Quality engineering (general quality)

The Quest Medical interview process

Quest Medical candidates report 3 rounds over 3-5 weeks. The stages below are what candidates describe, not a published process.

Phone Screen

Brief, casual call with a recruiter to review your background, qualifications, and initial interest in the company.

What to demonstrate

Brief, casual call with a recruiter to review your background, qualifications, and initial interest in the company
Depth in Cleanroom/sterilization processes

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.

Initial Technical Discussion

One-on-one technical discussion or campus interview if applying through a university pipeline.

What to demonstrate

One-on-one technical discussion or campus interview if applying through a university pipeline
Depth in Cleanroom/sterilization processes

How to prepare

Answer aloud and timed: What experience do you have working with hardware-software integration or testing physical devices?
Answer aloud and timed: How do you ensure code quality and reliability when working on critical systems?

On-site Interview

Intensive, multi-hour interview at the Quest Medical facility, starting with a tour and followed by back-to-back interviews with various professionals.

What to demonstrate

Intensive, multi-hour interview at the Quest Medical facility, starting with a tour and followed by back-to-back interviews with various professionals
Depth in Cleanroom/sterilization processes

How to prepare

Answer aloud and timed: Tell me about a time you had to learn a new tool or technology quickly to complete a project.
Answer aloud and timed: At Quest Medical, engineers are often expected to assist with various site-level tasks and physical device testing. How do you feel about carrying out diverse, hands-on work on-site?

Where candidates lose points

Prepare for a Marathon Onsite

The onsite interview is exceptionally long, often lasting up to five hours. Make sure to eat a hearty meal beforehand, bring a bottle of water, and pace your energy so you remain engaged and enthusiastic during the final hours of the day.

Highlight Your Versatility

During your interviews, actively emphasize your willingness to step outside of a pure coding environment. Share examples of times you helped with physical testing, collaborated with hardware teams, or assisted with on-site troubleshooting.

Follow Up Proactively

Because the recruiting and HR processes can sometimes experience delays or coordination challenges, do not hesitate to send polite, professional follow-up emails to your recruiter to check on your application status.

Questions & practice

Find overlapping job attempts and peak concurrency from lease records

Medium · sweep line · intervals · leases

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?

Canonicalise a request body into a stable idempotency fingerprint

Medium · parsing · canonicalisation · hashing

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?

Merge partitioned event streams into one ordered feed with bounded lateness

Hard · k-way merge · watermarks · out-of-order streams

The read-model service consumes 64 log partitions carrying about 4,000 events per second in total. Each partition is ordered within itself, but partitions drift by up to 30 seconds, and the activity feed must present a tenant's events in occurred_at order. Produce the merge. State its complexity, the buffer it requires in events and in bytes, what happens when one partition is idle, and what you do with an event that arrives after you have already emitted its position. Payloads average 1 KB.

Approach

Merge with a min-heap over the 64 partition heads keyed on (occurred_at, event_id): O(log P) per event and O(n log P) overall. The tie-break on event_id is what makes the output deterministic when two partitions carry the same millisecond, which matters because the feed is paginated and a non-deterministic order reorders pages under the reader.
Emitting the heap head is only correct once every partition has produced everything up to that timestamp, so the emit condition is a watermark: the minimum across partitions of the highest occurred_at seen, less the allowed lateness. Events are held until the watermark passes them, which is what turns individually ordered streams into a jointly ordered one.
Size the buffer from the lateness rather than guessing: 4,000 events per second times 30 seconds is 120,000 buffered events, and at 1 KB each about 120 MB of heap. That number is the real price of the ordering guarantee and belongs in front of whoever asked for it.
Handle the idle partition explicitly, because it fails the feed rather than corrupting it: a partition with no traffic never advances its own maximum, so the watermark freezes and output stops entirely. Either every partition emits a periodic idle marker carrying the broker's current time, or the watermark falls back to wall clock for a partition silent beyond a threshold.

Follow-up

The lateness budget is raised to five minutes. What is the new buffer, and what besides memory changes?
The consumer restarts. Where does it resume from, and what does the feed look like for the first 30 seconds?

Stop tag and share joins from fanning out a page

Medium · join fan-out · semi-joins · many-to-many

resource_tag is (resource_id, tag_id) with PK (resource_id, tag_id); resource_share is (resource_id, shared_with_user_id, permission). The tagged-and-shared listing inner-joins resource to both, filters tenant_id, tag_id = ANY($2) and shared_with_user_id = $3, orders by updated_at DESC and takes 50. Pages come back with fewer than 50 distinct resources and the total in the header is far too high. Explain the row multiplication, rewrite both the page query and the count query so each is correct, and name the index each one needs. PostgreSQL 16.

Approach

Do the arithmetic against the predicates that are actually there. An inner join emits one row per matching child row, and both joins are filtered: tag_id = ANY($2) admits only the requested tags, shared_with_user_id = $3 admits one user's share rows. So a resource holding three of the requested tags and shared with $3 once yields three rows, not one — the multiplier is its count of matching tags times its share rows for that single user, and that second factor is 1 unless the table admits duplicate (resource_id, shared_with_user_id) pairs. LIMIT 50 then limits rows rather than resources, and COUNT(*) counts pairs — the header is the product, not the population.
Reject DISTINCT as the fix. It deduplicates after the product has been built, so the planner must materialise and sort the fanned-out set before the LIMIT can apply, and it leaves any SUM or AVG in the same select list wrong.
Rewrite both filters as semi-joins, keeping resource as the only row source: AND EXISTS (SELECT 1 FROM resource_tag rt WHERE rt.resource_id = r.resource_id AND rt.tag_id = ANY($2)) and the same shape against resource_share. A semi-join stops at the first match per resource and preserves the driving index order, so ORDER BY updated_at DESC, resource_id DESC LIMIT 50 still stops after 50 rows.
Count with the same predicates and no join at all: SELECT count(*) FROM resource r WHERE r.tenant_id = $1 AND r.status = 'active' AND EXISTS (...) AND EXISTS (...). Nothing multiplies a resource, so the number is the population.

Follow-up

The filter changes from 'any of these tags' to 'all of these tags'. Rewrite it and state what it costs relative to the ANY form.
A resource can be shared with the same user twice under different permissions. Does your count change, and should it?

Find version gaps and relay lag with window functions

Medium · window functions · event tables · frame semantics

outbox_event holds event_id, aggregate_type, aggregate_id, aggregate_version, event_type, payload, status ('pending','published','dead'), attempts, created_at, published_at. A projection is missing rows and you must decide whether the relay skipped events or the consumer dropped them. Write three queries over the last seven days: one listing every aggregate_id whose published aggregate_version sequence has a hole, one giving per-day counts with a running total, and one returning the newest published event per aggregate. For each, say where the window function is evaluated relative to WHERE and LIMIT. PostgreSQL 16.

Approach

Gaps: compute lead(aggregate_version) OVER (PARTITION BY aggregate_id ORDER BY aggregate_version) in a subquery, then filter next_version <> aggregate_version + 1 in the outer query. Window functions are evaluated after WHERE, GROUP BY and HAVING and before the outer ORDER BY and LIMIT, so the predicate cannot sit in the same WHERE clause and PostgreSQL 16 has no QUALIFY.
Say what the seven-day filter does to the answer: it truncates every partition, so the first row per aggregate has no predecessor inside the window and a hole spanning the boundary is invisible. Widen the window, or join to resource.version as the authority for the true maximum.
Running total: SELECT date_trunc('day', created_at) AS d, count() AS n, sum(count()) OVER (ORDER BY date_trunc('day', created_at) ROWS UNBOUNDED PRECEDING). An aggregate inside a window call is legal because grouping runs before windowing. The grouping key is unique per row here so ROWS and RANGE agree, but write the frame anyway — over ungrouped rows with tied timestamps the default RANGE frame pulls in every peer row and the total jumps.
Newest per aggregate: DISTINCT ON (aggregate_id) ... ORDER BY aggregate_id, aggregate_version DESC is the cheap PostgreSQL-only form when an index matches that order; row_number() OVER (PARTITION BY aggregate_id ORDER BY aggregate_version DESC) = 1 is the portable form and needs a subquery for the same evaluation-order reason as the gap query.

Follow-up

Relay failover redelivers events. Does a duplicate break the gap query, and how would you detect one from this table alone?
Turn the gap check into a continuous monitor rather than a query someone runs after an incident. What does it watch?

Describe a challenging software bug you encountered in a past project and how you went about diagnosing and re

Medium · Background & Resume Deep-Dive

Describe a challenging software bug you encountered in a past project and how you went about diagnosing and resolving 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?

What experience do you have working with hardware-software integration or testing physical devices?

Medium · Background & Resume Deep-Dive

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 ensure code quality and reliability when working on critical systems?

Medium · Background & Resume Deep-Dive

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?

At Quest Medical, engineers are often expected to assist with various site-level tasks and physical device tes

Medium · Cross-Functional & On-Site Adaptability

At Quest Medical, engineers are often expected to assist with various site-level tasks and physical device testing. How do you feel about carrying out diverse, hands-on work on-site?

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 had to work closely with manufacturing, quality assurance, or field service tea

Medium · Cross-Functional & On-Site Adaptability

Describe a situation where you had to work closely with manufacturing, quality assurance, or field service teams. How did you manage communication?

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 explain complex technical software concepts to stakeholders who do not have a background in softwar

Medium · Cross-Functional & On-Site Adaptability

How do you explain complex technical software concepts to stakeholders who do not have a background in software development?

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 troubleshooting a software issue when you suspect the root cause might actually be a hardw

Medium · Cross-Functional & On-Site Adaptability

How do you approach troubleshooting a software issue when you suspect the root cause might actually be a hardware failure?

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?

Suggested practice checklist

Built from the rounds and topics Quest Medical candidates report.

Day 1 — Map the Quest Medical loop

Write out the reported sequence: Phone Screen, Initial Technical Discussion, On-site Interview.
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.

Day 2 — Work Cleanroom/sterilization processes

Spend the session on Cleanroom/sterilization processes, which Quest Medical candidates report being tested on.
Write one worked example in Cleanroom/sterilization processes and time yourself on it.

Deliverable: One timed worked example in Cleanroom/sterilization processes.

Day 3 — Work Medical device / disposables domain knowledge

Spend the session on Medical device / disposables domain knowledge, which Quest Medical candidates report being tested on.
Write one worked example in Medical device / disposables domain knowledge and time yourself on it.

Deliverable: One timed worked example in Medical device / disposables domain knowledge.

Day 4 — Work Quality engineering (general quality)

Spend the session on Quality engineering (general quality), which Quest Medical candidates report being tested on.
Write one worked example in Quality engineering (general quality) and time yourself on it.

Deliverable: One timed worked example in Quality engineering (general quality).

Day 5 — Answer out loud: Background & Resume Deep-Dive

Answer aloud, timed: Walk me through your resume and explain your experience with [specific technology/programming language mentioned in your background].
Answer aloud, timed: Describe a challenging software bug you encountered in a past project and how you went about diagnosing and resolving it.

Deliverable: Spoken answers to 2 reported Background & Resume Deep-Dive question(s), under time.

Day 6 — Answer out loud: Cross-Functional & On-Site Adaptability

Answer aloud, timed: At Quest Medical, engineers are often expected to assist with various site-level tasks and physical device testing. How do you feel about carrying out diverse, hands-on work on-site?
Answer aloud, timed: Describe a situation where you had to work closely with manufacturing, quality assurance, or field service teams. How did you manage communication?

Deliverable: Spoken answers to 2 reported Cross-Functional & On-Site Adaptability question(s), under time.

Day 7 — Answer out loud: Behavioral & Cultural Alignment

Answer aloud, timed: Why do you want to work at Quest Medical, and how does your background align with the medical device industry?
Answer aloud, timed: How do you handle repetitive questions or maintain your energy during a long, multi-hour interview panel with different teams?

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

Behavioural preparation

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

Walk me through your resume and explain your experience with [specific technology/programming language mention

Medium · Background & Resume Deep-Dive

Walk me through your resume and explain your experience with [specific technology/programming language mentioned in your background].

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 learn a new tool or technology quickly to complete a project.

Medium · Background & Resume Deep-Dive

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?

Explain a time when you had to adapt to a sudden change in project requirements or priorities.

Medium · Cross-Functional & On-Site Adaptability

Approach

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

Follow-up

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

Why do you want to work at Quest Medical, and how does your background align with the medical device industry?

Medium · Behavioral & Cultural Alignment

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 repetitive questions or maintain your energy during a long, multi-hour interview panel with

Medium · Behavioral & Cultural Alignment

How do you handle repetitive questions or maintain your energy during a long, multi-hour interview panel with different teams?

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 time when you disagreed with a colleague on a technical approach. How did you resolve the conflict?

Medium · Behavioral & Cultural Alignment

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 tasks when managing multiple competing deadlines?

Medium · Behavioral & Cultural Alignment

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?