cswork / libraryOpen practice workspace

Interview guides · Presbyterian Healthcare Services

Presbyterian Healthcare Services Software Engineer Interview Guide

Presbyterian Healthcare Services Software Engineer interview guide: reported rounds, questions and how candidates describe the process.

The 60-second brief

As a Software Engineer at Presbyterian Healthcare Services, you play a vital role in building and maintaining the technical infrastructure that supports patient care and operational workflows across healthcare facilities. This position directly impacts administrative systems, clinical data pipelines, and remote healthcare applications that serve communities throughout New Mexico. Your work bridges the gap between complex healthcare data and reliable, user-friendly software solutions that empower medical professionals to deliver exceptional care. You will contribute to critical problem spaces ranging from enterprise reporting and data warehousing platforms like Caboodle to specialized remote facility coding and data management applications.

This guide is scoped to a Software Engineer candidate at Presbyterian Healthcare Services.

Focus areas

  • ICD Coding
  • Credentialing/Medical Coding Terminology (CCS)
  • Facility-based Coding (IP Facility / PCS-ICD)

The Presbyterian Healthcare Services interview process

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

Initial Screening

The first step involves a review of your application and qualifications.

What to demonstrate

  • The first step involves a review of your application and qualifications
  • Depth in ICD Coding

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 Interviews

You will participate in interviews focused on assessing your technical capabilities.

What to demonstrate

  • You will participate in interviews focused on assessing your technical capabilities
  • Depth in ICD Coding

How to prepare

  • Answer aloud and timed: How do you ensure data integrity and security when integrating external systems into a centralized platform?
  • Answer aloud and timed: What steps do you take to troubleshoot performance bottlenecks in a multi-user remote application environment?

Final Interview

A potential final interview with team leads or management to evaluate cultural fit and collaboration.

What to demonstrate

  • A potential final interview with team leads or management to evaluate cultural fit and collaboration
  • Depth in ICD Coding

How to prepare

  • Answer aloud and timed: Explain how you approach code version control, testing, and deployment in a regulated technical environment.
  • Answer aloud and timed: This category tests how you diagnose complex issues, structure troubleshooting steps, and maintain system reliability.

Where candidates lose points

Emphasize reliability and precision

In healthcare technology, stability and accuracy are just as important as speed. Highlight your commitment to thorough testing and secure data management in your answers.

Structure your troubleshooting stories

Use a clear narrative framework when discussing past incidents, detailing the diagnostic steps, the root cause analysis, and the long-term preventive measures you implemented.

Connect technology to operational impact

Always ground your technical explanations in how your work supports end-users and organizational efficiency.

Prepare for stakeholder scenarios

Expect questions about how you manage requests from non-technical departments and practice explaining complex technical issues in plain language.

Review your core fundamentals

Refresh your knowledge of database management, query performance tuning, and application support principles before your technical conversations.

Questions & practice

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

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

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

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

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

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

Describe an instance where you had to refactor legacy code or optimize a slow-running query. What was your str

Medium · Problem-Solving and System Administratio

Describe an instance where you had to refactor legacy code or optimize a slow-running query. What was your strategy?

Approach

  1. Name the grain you start from and join outward from it.
  2. Check whether any join is one-to-many before aggregating, or the sums inflate.
  3. Say which index the query would use, and what makes it unusable.
  4. Handle the rows that do not match: that is usually the actual question.

Follow-up

  • How does the query change if that join becomes one-to-many?
  • What happens to this when the table is ten times larger?

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

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

This category evaluates your foundational technical knowledge, familiarity with healthcare data systems, and a

Medium · Technical and Domain Expertise

This category evaluates your foundational technical knowledge, familiarity with healthcare data systems, and ability to manage application infrastructure.

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 do you ensure data integrity and security when integrating external systems into a centralized platform?

Medium · Technical and Domain Expertise

Approach

  1. Say who the caller is and what they do when the call fails halfway.
  2. Define the identity of a request so a retry cannot double-apply it.
  3. Separate accepted, pending, failed and confirmed; they are different facts.
  4. 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 approach code version control, testing, and deployment in a regulated technical environment.

Medium · Technical and Domain Expertise

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?

Walk us through a time when a critical reporting or application pipeline failed in production. How did you dia

Medium · Problem-Solving and System Administratio

Walk us through a time when a critical reporting or application pipeline failed in production. How did you diagnose and resolve it?

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 do you prioritize competing technical tasks when supporting multiple clinical or administrative user group

Medium · Problem-Solving and System Administratio

How do you prioritize competing technical tasks when supporting multiple clinical or administrative user groups?

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?

This category assesses your ability to work alongside non-technical staff, clinical teams, and cross-functiona

Medium · Collaboration and Stakeholder Communicat

This category assesses your ability to work alongside non-technical staff, clinical teams, and cross-functional engineering partners.

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 do you gather requirements from stakeholders who may not have a technical background?

Medium · Collaboration and Stakeholder Communicat

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?

Describe a situation where you had to explain a complex technical problem or system outage to executive leader

Medium · Collaboration and Stakeholder Communicat

Describe a situation where you had to explain a complex technical problem or system outage to executive leadership.

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?

What steps do you take to troubleshoot performance bottlenecks in a multi-user remote application environment?

Medium · Technical and Domain Expertise

Approach

  1. Establish what changed and when, before forming any theory.
  2. Pick a bisection that eliminates candidates whichever way it turns out.
  3. Check the instrumentation before believing the symptom.
  4. 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?

This category tests how you diagnose complex issues, structure troubleshooting steps, and maintain system reli

Medium · Problem-Solving and System Administratio

This category tests how you diagnose complex issues, structure troubleshooting steps, and maintain system reliability.

Approach

  1. Establish what changed and when, before forming any theory.
  2. Pick a bisection that eliminates candidates whichever way it turns out.
  3. Check the instrumentation before believing the symptom.
  4. 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 Presbyterian Healthcare Services candidates report.

Day 1 — Map the Presbyterian Healthcare Services loop

  • Write out the reported sequence: Initial Screening, Technical Interviews, Final 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 ICD Coding

  • Spend the session on ICD Coding, which Presbyterian Healthcare Services candidates report being tested on.
  • Write one worked example in ICD Coding and time yourself on it.

Deliverable: One timed worked example in ICD Coding.

Day 3 — Work Credentialing/Medical Coding Terminology (CCS)

  • Spend the session on Credentialing/Medical Coding Terminology (CCS), which Presbyterian Healthcare Services candidates report being tested on.
  • Write one worked example in Credentialing/Medical Coding Terminology (CCS) and time yourself on it.

Deliverable: One timed worked example in Credentialing/Medical Coding Terminology (CCS).

Day 4 — Work Facility-based Coding (IP Facility / PCS-ICD)

  • Spend the session on Facility-based Coding (IP Facility / PCS-ICD), which Presbyterian Healthcare Services candidates report being tested on.
  • Write one worked example in Facility-based Coding (IP Facility / PCS-ICD) and time yourself on it.

Deliverable: One timed worked example in Facility-based Coding (IP Facility / PCS-ICD).

Day 5 — Answer out loud: Technical and Domain Expertise

  • Answer aloud, timed: This category evaluates your foundational technical knowledge, familiarity with healthcare data systems, and ability to manage application infrastructure.
  • Answer aloud, timed: Describe your experience administering enterprise data warehouse applications or managing database schemas.

Deliverable: Spoken answers to 2 reported Technical and Domain Expertise question(s), under time.

Day 6 — Answer out loud: Problem-Solving and System Administration

  • Answer aloud, timed: This category tests how you diagnose complex issues, structure troubleshooting steps, and maintain system reliability.
  • Answer aloud, timed: Walk us through a time when a critical reporting or application pipeline failed in production. How did you diagnose and resolve it?

Deliverable: Spoken answers to 2 reported Problem-Solving and System Administration question(s), under time.

Day 7 — Answer out loud: Collaboration and Stakeholder Communication

  • Answer aloud, timed: This category assesses your ability to work alongside non-technical staff, clinical teams, and cross-functional engineering partners.
  • Answer aloud, timed: How do you gather requirements from stakeholders who may not have a technical background?

Deliverable: Spoken answers to 2 reported Collaboration and Stakeholder Communication question(s), under time.

Behavioural preparation

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

Describe your experience administering enterprise data warehouse applications or managing database schemas.

Medium · Technical and Domain Expertise

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 conflicting priorities between rapid feature delivery and rigorous system compliance?

Medium · Collaboration and Stakeholder Communicat

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?

Ship under a deadline and bound the debt you chose

Medium · pagination · technical debt · tradeoffs

You have four days to ship a tenant-facing listing endpoint. The version you would defend uses keyset pagination over (tenant_id, status, updated_at DESC, resource_id DESC); the version you can finish uses LIMIT/OFFSET with no matching index. Describe a deadline call you actually made of this shape: what you shipped, what you knowingly deferred, how you bounded the damage with a mechanism rather than an intention, and the specific numeric condition that would force the follow-up. Name who you told and where you wrote it down.

Approach

  1. Name the deferred failure precisely instead of calling it slow. OFFSET n makes the database produce and discard n rows, so cost grows with page depth; without an index matching the sort, every matching row is read and sorted before the limit applies; and rows inserted between two page fetches shift across the boundary so items are skipped or repeated with nothing in the response to signal it.
  2. Bound the blast radius with something mechanical rather than a promise: cap maximum page depth, cap page size, restrict the endpoint to one internal caller, or keep it behind a flag. State which failure each cap removes and which it leaves standing.
  3. Attach a number to the trigger and wire it to an alarm: the first tenant crossing N resources, or the endpoint's p99 crossing its share of the 400 ms budget, so the debt announces itself instead of waiting to be remembered.
  4. Write it where the next engineer looks, which is the code and the ticket, not a chat message: what was deferred, why, the cap, and the trigger.

Follow-up

  • At what page depth does the offset version breach your latency budget, given your page size and row counts?
  • What breaks first when you switch to keyset pagination later, and what does a client holding an old page token see?