Interview guides · Orlando Health

Orlando Health Software Engineer Interview Guide

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

The 60-second brief

As a Software Engineer at Orlando Health, you are stepping into a role where technology directly intersects with patient care and clinical operations. This position is not just about writing code; it is about building, maintaining, and integrating the critical systems that healthcare professionals rely on every single day. Your work ensures that clinical data flows securely, medical applications function flawlessly, and hospital operations remain efficient. The impact of this position is profound. You will often work at the intersection of traditional software development and clinical engineering technology. The solutions you develop or support will directly influence the user experience of doctors, nurses, and administrative staff, ultimately affecting patient outcomes.

This guide is scoped to a Software Engineer candidate at Orlando Health.

Focus areas

Clinical Domain Knowledge (Healthcare/Clinical Engineering)
Software Engineering (General)
Phone Interview Skills (Hiring Screen)

The Orlando Health interview process

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

Recruiter Screen

Initial screening with a recruiter to assess basic qualifications and fit for the role.

What to demonstrate

Initial screening with a recruiter to assess basic qualifications and fit for the role
Depth in Clinical Domain Knowledge (Healthcare/Clinical Engineering)

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.

Panel Interviews

Multiple panel interviews with team members to discuss technical skills and past experiences.

What to demonstrate

Multiple panel interviews with team members to discuss technical skills and past experiences
Depth in Clinical Domain Knowledge (Healthcare/Clinical Engineering)

How to prepare

Answer aloud and timed: Describe a time you had to learn a new technology on the fly to complete a project.
Answer aloud and timed: How do you ensure your code is maintainable for future engineers?

Management Panel

Final panel interview with management to evaluate cultural fit and alignment with organizational values.

What to demonstrate

Final panel interview with management to evaluate cultural fit and alignment with organizational values
Depth in Clinical Domain Knowledge (Healthcare/Clinical Engineering)

How to prepare

Answer aloud and timed: Tell me about a project that failed or missed a deadline. What did you learn?
Answer aloud and timed: Describe a time you had to work with a difficult stakeholder. How did you manage the relationship?

Where candidates lose points

Connect Your Work to the Mission

Always frame your technical achievements in terms of user impact. At Orlando Health, the ultimate end-user is often a patient or a healthcare provider. Show that you care about the real-world results of your code.

Be Ready for Panel Dynamics

You will likely face panels of 3-4 people. Make eye contact (or address the camera directly if remote) with all members, and be prepared for rapid-fire questions from different perspectives, ranging from highly technical peers to management.

Prepare for Resume Scrutiny

Hiring managers at Orlando Health conduct thorough reviews of your submitted materials. Be prepared to speak in-depth about every technology, project, and certification listed on your resume.

Questions & practice

How do you balance the need to deliver a feature quickly versus writing perfect, optimized code?

Medium · Technical & Systems Problem Solving

Approach

Restate the input: its shape, its size, and what is guaranteed about it.
Name the brute-force solution and its complexity before improving on it.
Choose the data structure from the access pattern, not from familiarity.
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?

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?

Collapse a redelivered event batch into per-aggregate high-water marks

Easy · hashing · at-least-once · aggregation

You drain a batch of up to 5,000,000 events, each (aggregate_id BIGINT, aggregate_version INT, event_type, payload). The log guarantees order within one aggregate only; the batch merges 64 partitions, and a relay failover has redelivered a range, so an older version for an aggregate can appear after a newer one. Given a map of last_applied_version per aggregate, produce the events worth applying, at most one per (aggregate_id, version), plus the count discarded. Target O(n) time. State the memory for 2,000,000 distinct aggregates and what you do when it does not fit.

Approach

One pass, one hash map from aggregate_id to the highest version kept, and a discard counter. An event whose version is at or below last_applied_version for its aggregate is dropped without further work, which is the whole reason the event carries its version rather than a delta. O(n) expected time, O(d) space in distinct aggregates.
Keep the maximum, never the last occurrence. The redelivered range means the final appearance of an aggregate in the batch can be an older version than one seen earlier in the same batch, so last-wins applies stale state over newer state and the projection regresses with no error anywhere.
Cost the memory instead of calling it large: an 8-byte key plus a 4-byte version is 12 bytes of payload, and an open-addressed table held at a 0.7 load factor costs roughly 17 bytes per entry before per-slot metadata, so 2,000,000 aggregates is tens of megabytes in a native layout and several times that in a runtime that boxes both key and value.
If the distinct set exceeds memory, partition on hash(aggregate_id) mod P and reduce each partition independently. Every event for one aggregate hashes to the same partition, so the per-partition result is exact and the merge is concatenation rather than a second reduction.

Follow-up

The payload is a patch rather than a snapshot, so applying only the highest version loses the intermediate changes. What changes in your reduction?
How do you detect that version 7 arrived while version 6 was never delivered, and what should the consumer do about the gap?

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

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.
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.
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.
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?

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

Name the two failures separately. OFFSET 20000 makes the server produce and discard 20,000 rows, so page cost grows with depth rather than with page size. Independently, any write that changes how many rows sort above the offset moves the window between two fetches, and the direction decides which anomaly you get: an insert lands at the head of updated_at DESC and pushes already-returned rows down past the boundary, so they are returned a second time; a delete above the offset, or a row whose updated_at is bumped above the cursor, pulls rows up and one is never returned at all. Nothing in the response reveals either.
Write the seek: WHERE tenant_id = $1 AND status = 'active' AND (updated_at, resource_id) < ($2, $3) ORDER BY updated_at DESC, resource_id DESC LIMIT 50. The row-value comparison is one index range rather than a disjunction, and both columns are NOT NULL, which is what makes that comparison well defined.
Map each predicate onto the index: tenant_id and status are equality on the leading columns, (updated_at, resource_id) is the range, and the ORDER BY matches the index order so no Sort node appears and the scan stops after 50 rows. The DESC in the definition only matters for mixed directions — a plain ascending btree on the same columns is read backwards for this query.
Put both sort columns in the cursor and nothing the client can tamper with into another tenant: base64 of (updated_at, resource_id), validated server-side, with tenant_id taken from the principal.

Follow-up

The client asks for 'jump to page 400'. What do you offer instead, and what does the honest version cost?
Sort order becomes user-selectable across four columns. How many indexes is that, and which would you refuse to add?

Can you walk me through the architecture of the most complex application you have built?

Medium · Past Experience & Resume Deep Dive

Approach

Fix the scope first: who calls this, how often, and what they do when it fails.
Name the read and write paths separately; they rarely have the same bottleneck.
Choose a partition key and say what query it makes expensive.
State the consistency you need, and where you are willing to be stale.

Follow-up

What breaks first when traffic grows ten times?
How does this behave when that dependency is down for an hour?

What was your specific role in [Project Name], and what would you do differently if you had to build it again?

Medium · Past Experience & 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?

How do you ensure your code is maintainable for future engineers?

Medium · Past Experience & 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?

How do you approach integrating a modern web application with a legacy database?

Medium · Technical & Systems Problem Solving

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?

Explain how you design RESTful APIs. What are your best practices for security and versioning?

Medium · Technical & Systems Problem Solving

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?

Walk me through your process for debugging an application that is crashing intermittently in production.

Medium · Technical & Systems Problem Solving

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 Orlando Health candidates report.

Day 1 — Map the Orlando Health loop

Write out the reported sequence: Recruiter Screen, Panel Interviews, Management Panel.
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 Clinical Domain Knowledge (Healthcare/Clinical Engineering)

Spend the session on Clinical Domain Knowledge (Healthcare/Clinical Engineering), which Orlando Health candidates report being tested on.
Write one worked example in Clinical Domain Knowledge (Healthcare/Clinical Engineering) and time yourself on it.

Deliverable: One timed worked example in Clinical Domain Knowledge (Healthcare/Clinical Engineering).

Day 3 — Work Software Engineering (General)

Spend the session on Software Engineering (General), which Orlando Health candidates report being tested on.
Write one worked example in Software Engineering (General) and time yourself on it.

Deliverable: One timed worked example in Software Engineering (General).

Day 4 — Work Phone Interview Skills (Hiring Screen)

Spend the session on Phone Interview Skills (Hiring Screen), which Orlando Health candidates report being tested on.
Write one worked example in Phone Interview Skills (Hiring Screen) and time yourself on it.

Deliverable: One timed worked example in Phone Interview Skills (Hiring Screen).

Day 5 — Answer out loud: Past Experience & Resume Deep Dive

Answer aloud, timed: Can you walk me through the architecture of the most complex application you have built?
Answer aloud, timed: What was your specific role in [Project Name], and what would you do differently if you had to build it again?

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

Day 6 — Answer out loud: Behavioral & Cultural Fit

Answer aloud, timed: Describe a time you had to work with a difficult stakeholder. How did you manage the relationship?
Answer aloud, timed: How do you handle situations where project requirements are vague or constantly changing?

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

Day 7 — Answer out loud: Technical & Systems Problem Solving

Answer aloud, timed: Walk me through your process for debugging an application that is crashing intermittently in production.
Answer aloud, timed: How do you approach integrating a modern web application with a legacy database?

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

Behavioural preparation

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

Describe a time you had to learn a new technology on the fly to complete a project.

Medium · Past Experience & 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?

Tell me about a project that failed or missed a deadline. What did you learn?

Medium · Past Experience & 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?