University of North Texas - Health Science Center Software Engineer Interview Guide

The 60-second brief

At the University of North Texas - Health Science Center, a Software Engineer plays a pivotal role in bridging the gap between cutting-edge medical education, clinical research, and robust technology solutions. This position is not just about writing code; it is about building and maintaining the digital infrastructure that empowers researchers, healthcare professionals, educators, and students. The systems you develop and support directly impact clinical workflows, academic portals, and data-driven scientific discoveries that improve public health outcomes. As a Software Engineer in this unique healthcare and academic environment, you will work on a diverse array of projects. These range from public-facing web applications and internal administrative platforms to complex databases handling sensitive research data.

This guide is scoped to a Software Engineer candidate at University of North Texas - Health Science Center.

Focus areas

• Coding Interview Practice
• Algorithmic Problem Solving
• Behavioral Interviewing

The University of North Texas - Health Science Center interview process

University of North Texas - Health Science Center candidates report 3 rounds over 3-5 weeks. The stages below are what candidates describe, not a published process.

HR Screening

Initial screening or brief phone interview to review background, experience, and alignment with the role.

What to demonstrate

• Initial screening or brief phone interview to review background, experience, and alignment with the role
• Depth in Coding Interview Practice

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

Assessment may include online aptitude tests, logical reasoning, or basic coding challenges.

What to demonstrate

• Assessment may include online aptitude tests, logical reasoning, or basic coding challenges
• Depth in Coding Interview Practice

How to prepare

• Answer aloud and timed: How do you optimize web page performance using HTML, CSS, and client-side scripting?
• Answer aloud and timed: Describe the basics of computer fundamentals, including memory management and database indexing.

In-Depth Interviews

Interviews conducted virtually or in-person with the department manager, team members, and sometimes the entire office panel.

What to demonstrate

• Interviews conducted virtually or in-person with the department manager, team members, and sometimes the entire office panel
• Depth in Coding Interview Practice

How to prepare

• Answer aloud and timed: Walk me through a basic data structure implementation, such as a queue or a linked list.
• Answer aloud and timed: Walk me through the most technically challenging project on your resume. What was your role, and how did you overcome the primary bottleneck?

Where candidates lose points

Showcase your full-stack versatility

Since the engineering team supports a wide variety of institutional needs, highlighting your comfort with both frontend (HTML/CSS/JavaScript) and backend technologies will make you a highly attractive candidate.

Prepare for a panel format

You may face an interview where the entire local office or department sits in on the conversation. Do not let this intimidate you; it is designed to be a friendly, conversational introduction to the team you will be working with daily.

If your interviewers seem busy or distracted during your session, do not take it personally

University IT departments often handle high volumes of support tickets and system deployments simultaneously. Maintain your enthusiasm and deliver your answers professionally.

Highlight your communication skills

In an academic health science center, you will frequently interact with non-technical stakeholders. Emphasize your ability to translate complex technical jargon into clear, actionable business terms during your behavioral answers.

Questions & practice

Write a program or algorithm to simulate shuffling a deck of cards.

Medium · Technical & Coding Fundamentals

Approach

1. Restate the input: its shape, its size, and what is guaranteed about it.
2. Name the brute-force solution and its complexity before improving on it.
3. Choose the data structure from the access pattern, not from familiarity.
4. State the target complexity and say which constraint rules the naive version out.

Follow-up

• How does this change if the input no longer fits in memory?
• What is the worst case, and how likely is it on real data?

Explain the core differences between web frameworks like Django and Ruby on Rails.

Medium · Technical & Coding Fundamentals

Approach

1. Restate the input: its shape, its size, and what is guaranteed about it.
2. Name the brute-force solution and its complexity before improving on it.
3. Choose the data structure from the access pattern, not from familiarity.
4. State the target complexity and say which constraint rules the naive version out.

Follow-up

• How does this change if the input no longer fits in memory?
• What is the worst case, and how likely is it on real data?

How do you optimize web page performance using HTML, CSS, and client-side scripting?

Medium · Technical & Coding Fundamentals

Approach

1. Restate the input: its shape, its size, and what is guaranteed about it.
2. Name the brute-force solution and its complexity before improving on it.
3. Choose the data structure from the access pattern, not from familiarity.
4. State the target complexity and say which constraint rules the naive version out.

Follow-up

• How does this change if the input no longer fits in memory?
• What is the worst case, and how likely is it on real data?

Describe the basics of computer fundamentals, including memory management and database indexing.

Medium · Technical & Coding Fundamentals

Approach

1. Say what the runtime actually does before reasoning about the code.
2. Name what is shared across threads and what owns each piece of state.
3. Identify the window where an invariant is briefly untrue.
4. Distinguish a value from a reference to it, and say which one you handed out.

Follow-up

• What happens if two callers reach this at the same time?
• Where could this allocate more than you expect?

Walk me through a basic data structure implementation, such as a queue or a linked list.

Medium · Technical & Coding Fundamentals

Approach

1. Restate the input: its shape, its size, and what is guaranteed about it.
2. Name the brute-force solution and its complexity before improving on it.
3. Choose the data structure from the access pattern, not from familiarity.
4. State the target complexity and say which constraint rules the naive version out.

Follow-up

• How does this change if the input no longer fits in memory?
• What is the worst case, and how likely is it on real data?

Replace offset paging on the resource feed with keyset

Easy · keyset pagination · composite index · sort order

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

1. 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.
2. 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.
3. 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.
4. 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?

Explain why the owner filter ignores the listing index

Medium · composite index · query plans · sort elimination

The only index on resource is (tenant_id, status, updated_at DESC, resource_id DESC). A new endpoint returns one user's resources across all statuses, newest created first: WHERE tenant_id = $1 AND owner_user_id = $2 ORDER BY created_at DESC LIMIT 20. On a tenant with 2M rows it takes 900 ms and EXPLAIN shows a sort above a large scan. Explain precisely why the existing index cannot serve it, give the index that can, and state which of these the new index still will not help: owner_user_id alone across tenants; the same query ordered by updated_at. PostgreSQL 16.

Approach

1. Separate the two jobs an index does. For filtering, a composite btree is seekable only on a left prefix, so with no predicate on status the scan can at best range over tenant_id and test owner_user_id per row; PostgreSQL 16 has no btree skip scan to jump the unconstrained column.
2. For ordering, the index is sorted by (status, updated_at) within a tenant and not by created_at, so the LIMIT cannot stop early: every matching row is read and then sorted. That is the 'Sort Method: top-N heapsort' line, and it is why the plan reads 2M rows to answer with 20.
3. Derive the replacement from the access path — equality, equality, then the ordering column: CREATE INDEX CONCURRENTLY ON resource (tenant_id, owner_user_id, created_at DESC). The scan seeks to the (tenant, owner) range and walks 20 entries in order, so the Sort node disappears along with the row-read.
4. Treat INCLUDE (title, status) as conditional, not free. An index-only scan still visits the heap for any row whose page is not marked all-visible, so on a table taking 1.2k writes/second the win depends on autovacuum keeping the visibility map current, and the wider index costs more on every insert.

Follow-up

• 90% of rows are status='active'. Would a partial index WHERE status = 'active' change your answer, and for which of the three queries?
• A dashboard runs this for 40 owners in one page load. What changes about the design?

Walk me through the most technically challenging project on your resume. What was your role, and how did you o

Medium · Resume & Project Walkthroughs

Walk me through the most technically challenging project on your resume. What was your role, and how did you overcome the primary bottleneck?

Approach

1. Clarify what is being asked and what a complete answer contains.
2. State your assumptions explicitly before working the problem.
3. Say what you would check first and why it is the highest-information step.
4. 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 many software projects have you taken from conception to deployment, and what technologies did you use?

Medium · Resume & Project Walkthroughs

Approach

1. Clarify what is being asked and what a complete answer contains.
2. State your assumptions explicitly before working the problem.
3. Say what you would check first and why it is the highest-information step.
4. Work from the requirement backwards to the design.

Follow-up

• What assumption would you test first?
• How would you know your answer was wrong?

Edge instances grow 400 MB per hour until the nightly restart

Hard · memory leak · heap analysis · metric cardinality

Edge API instances start at 700 MB resident and grow about 400 MB/hour; a nightly rolling restart has hidden it for weeks. Growth continues unchanged when request rate halves overnight, p99 degrades in the last hours before an instance is recycled, and heap used immediately after a forced full GC rises monotonically. The service holds no product state. Name the discriminating measurement that separates the plausible causes, give the most likely cause, and give the fix and how you would verify it.

Approach

1. Separate resident memory from live heap first, because they fail differently. Resident size can grow from fragmentation, native buffers or thread stacks while the heap is flat; heap used after a full GC rising monotonically is the measurement that says objects are reachable and not being released. You already have it, so this is retention, not fragmentation, and that closes off half the candidate list.
2. Use the rate's independence from traffic as the discriminator. Growth that continues at half the request rate rules out per-request objects that are merely slow to collect and points at a structure that grows with distinct values observed rather than with call volume. Write the candidates that have that property: a metrics registry keyed on a high-cardinality label, an unevicted cache, an interner, a per-key lock map.
3. Take two heap snapshots an hour apart and diff by retained size, reading the dominator tree, not by allocation count or instance count. Expect one root holding a map with millions of entries, then follow the reference chain to the code that inserts and never removes. Allocation profilers point at churn, which is the wrong signal here.
4. The candidate that fits this service is an observability label carrying an identifier, such as a request path recorded before templating so that /v1/resources/48213 becomes its own metric series. That grows with distinct ids seen, is independent of rate, and explains the late p99 degradation, since GC cost rises with the size of the live set.

Follow-up

• Post-GC heap is now flat but resident size still creeps. What are you looking at, and does it matter?
• How would you have detected this before an OOM, given the nightly restart masked the trend?

Suggested practice checklist

Built from the rounds and topics University of North Texas - Health Science Center candidates report.

Day 1 — Map the University of North Texas - Health Science Center loop

• Write out the reported sequence: HR Screening, Technical Assessment, In-Depth Interviews.
• 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 Coding Interview Practice

• Spend the session on Coding Interview Practice, which University of North Texas - Health Science Center candidates report being tested on.
• Write one worked example in Coding Interview Practice and time yourself on it.

Deliverable: One timed worked example in Coding Interview Practice.

Day 3 — Work Algorithmic Problem Solving

• Spend the session on Algorithmic Problem Solving, which University of North Texas - Health Science Center candidates report being tested on.
• Write one worked example in Algorithmic Problem Solving and time yourself on it.

Deliverable: One timed worked example in Algorithmic Problem Solving.

Day 4 — Work Behavioral Interviewing

• Spend the session on Behavioral Interviewing, which University of North Texas - Health Science Center 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.

Day 5 — Answer out loud: Technical & Coding Fundamentals

• Answer aloud, timed: Write a program or algorithm to simulate shuffling a deck of cards.
• Answer aloud, timed: Explain the core differences between web frameworks like Django and Ruby on Rails.

Deliverable: Spoken answers to 2 reported Technical & Coding Fundamentals question(s), under time.

Day 6 — Answer out loud: Resume & Project Walkthroughs

• Answer aloud, timed: Walk me through the most technically challenging project on your resume. What was your role, and how did you overcome the primary bottleneck?
• Answer aloud, timed: How many software projects have you taken from conception to deployment, and what technologies did you use?

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

Day 7 — Answer out loud: Behavioral & Professional Ethics

• Answer aloud, timed: Describe a situation where you had to explain a complex technical concept to a non-technical stakeholder, such as a medical researcher or academic administrator.
• Answer aloud, timed: How do you handle a situation where team members have conflicting opinions on a technical implementation?

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

Behavioural preparation

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

Describe a time when you had to work with a legacy codebase. How did you ensure your new code did not break ex

Medium · Resume & Project Walkthroughs

Describe a time when you had to work with a legacy codebase. How did you ensure your new code did not break existing functionality?

Approach

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

Follow-up

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

What is your experience level with database design and writing complex SQL queries?

Medium · Resume & Project Walkthroughs

Approach

1. Pick a story where you made the decision, not one where you watched it.
2. State the situation in two sentences and spend the rest on the reasoning.
3. Give the blast radius: what could have broken, and what you measured.
4. 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 explain a complex technical concept to a non-technical stakeholder, such

Medium · Behavioral & Professional Ethics

Describe a situation where you had to explain a complex technical concept to a non-technical stakeholder, such as a medical researcher or academic administrator.

Approach

1. Pick a story where you made the decision, not one where you watched it.
2. State the situation in two sentences and spend the rest on the reasoning.
3. Give the blast radius: what could have broken, and what you measured.
4. 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 a situation where team members have conflicting opinions on a technical implementation?

Medium · Behavioral & Professional Ethics

Approach

1. Pick a story where you made the decision, not one where you watched it.
2. State the situation in two sentences and spend the rest on the reasoning.
3. Give the blast radius: what could have broken, and what you measured.
4. 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?

Give an example of a time you had to make an ethical decision during a software development lifecycle.

Medium · Behavioral & Professional Ethics

Approach

1. Pick a story where you made the decision, not one where you watched it.
2. State the situation in two sentences and spend the rest on the reasoning.
3. Give the blast radius: what could have broken, and what you measured.
4. 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 manage your workload and maintain productivity when working on multiple projects with competing dea

Medium · Behavioral & Professional Ethics

How do you manage your workload and maintain productivity when working on multiple projects with competing deadlines?

Approach

1. Pick a story where you made the decision, not one where you watched it.
2. State the situation in two sentences and spend the rest on the reasoning.
3. Give the blast radius: what could have broken, and what you measured.
4. 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?