Fairview health services Software Engineer Interview Guide

The 60-second brief

A Software Engineer at Fairview health services plays a critical role in bridging the gap between cutting-edge technology and patient care. In a healthcare system of this scale, software is not just about efficiency; it directly impacts clinical workflows, data accessibility, and ultimately, patient outcomes. Engineers here build, optimize, and integrate applications that support thousands of clinicians, administrative staff, and patients across various clinics and hospitals. The work is highly impactful and intellectually challenging. You will be tasked with solving complex problems around data interoperability, system reliability, and secure information exchange.

This guide is scoped to a Software Engineer candidate at Fairview health services.

Focus areas

• Epic software experience
• Healthcare domain software
• Problem solving

The Fairview health services interview process

Fairview health services candidates report 4 rounds over 3-5 weeks. The stages below are what candidates describe, not a published process.

Initial Conversation

Discussion with a recruiter or hiring manager about background, interest in healthcare, and technical experience.

What to demonstrate

• Discussion with a recruiter or hiring manager about background, interest in healthcare, and technical experience
• Depth in Epic software experience

How to prepare

• Answer aloud and timed: Tell me about your experience working with Epic Software or other Electronic Health Record (EHR) platforms.
• Answer aloud and timed: How do you approach integrating custom internal applications with large-scale third-party enterprise systems?

Hiring Manager Interview

Interview focusing on high-level architecture, problem-solving, and behavioral alignment.

What to demonstrate

• Interview focusing on high-level architecture, problem-solving, and behavioral alignment
• Depth in Epic software experience

How to prepare

• Prepare two projects you led end to end, each with the decision you owned and what it cost.
• Have three questions about the team's roadmap and how success is measured in the first six months.

Engineering Team Interview

Interview with the engineering team and technical leads, focusing on practical engineering scenarios and code quality.

What to demonstrate

• Interview with the engineering team and technical leads
• Focusing on practical engineering scenarios and code quality

How to prepare

• Answer aloud and timed: Tell me about yourself and what draws you to software engineering in the healthcare sector.
• Answer aloud and timed: Describe a significant technical challenge you faced in a previous role. How did you identify the root cause, and what steps did you take to solve it?

Decision Making

Quick decision made after the final rounds are completed.

What to demonstrate

• Quick decision made after the final rounds are completed
• Depth in Epic software experience

How to prepare

• Answer aloud and timed: Tell me about a time when you had to work with a team member who had a different perspective on how to solve a technical problem. How did you reach a resolution?
• Answer aloud and timed: Give an example of a project where requirements changed mid-way through development. How did you adapt your approach?

Where candidates lose points

Connect Your Work to the Mission

When answering behavioral or technical questions, always keep the end-user in mind. Explain how your engineering decisions—such as optimizing a database query or securing an API—ultimately support clinicians and improve patient care.

Be prepared to discuss your experience with data security

In healthcare technology, understanding how to handle sensitive data securely is just as important as writing functional code.

Be Ready for the "Tell Me About Yourself" Question

Use this opening question to construct a compelling narrative. Highlight your technical journey, your experience with system integrations, and specifically why you want to apply your engineering skills to the healthcare sector at Fairview health services.

Use the STAR Method

For all behavioral questions regarding past challenges and problem-solving, structure your responses using the Situation, Task, Action, and Result framework. Focus heavily on the actions you personally took and the tangible results of your work.

Questions & practice

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

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

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

1. 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.
2. 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.
3. 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.
4. 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

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?

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?

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

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

How do you approach integrating custom internal applications with large-scale third-party enterprise systems?

Medium · Domain & System Integration

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?

Can you explain how you ensure data security and compliance (such as HIPAA) when developing software that hand

Medium · Domain & System Integration

Can you explain how you ensure data security and compliance (such as HIPAA) when developing software that handles sensitive patient information?

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?

How do you ensure your code is thoroughly tested before it is deployed to a production environment?

Medium · Technical Fundamentals & Code Quality

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 strategies do you use to optimize database performance or manage high volumes of transactional data?

Medium · Technical Fundamentals & Code Quality

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 methodologies do you use to troubleshoot data synchronization issues between two disparate software syste

Medium · Domain & System Integration

What methodologies do you use to troubleshoot data synchronization issues between two disparate software systems?

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?

Describe a significant technical challenge you faced in a previous role. How did you identify the root cause,

Medium · Behavioral & Problem-Solving

Describe a significant technical challenge you faced in a previous role. How did you identify the root cause, and what steps did you take to solve it?

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 Fairview health services candidates report.

Day 1 — Map the Fairview health services loop

• Write out the reported sequence: Initial Conversation, Hiring Manager Interview, Engineering Team Interview, Decision Making.
• For each round, write one sentence on what it is judging, from the description above, and mark the one you are least ready for.

Deliverable: A one-page map of the 4 reported rounds, with the weakest marked.

Day 2 — Work Epic software experience

• Spend the session on Epic software experience, which Fairview health services candidates report being tested on.
• Write one worked example in Epic software experience and time yourself on it.

Deliverable: One timed worked example in Epic software experience.

Day 3 — Work Healthcare domain software

• Spend the session on Healthcare domain software, which Fairview health services candidates report being tested on.
• Write one worked example in Healthcare domain software and time yourself on it.

Deliverable: One timed worked example in Healthcare domain software.

Day 4 — Work Problem solving

• Spend the session on Problem solving, which Fairview health services candidates report being tested on.
• Write one worked example in Problem solving and time yourself on it.

Deliverable: One timed worked example in Problem solving.

Day 5 — Answer out loud: Domain & System Integration

• Answer aloud, timed: Tell me about your experience working with Epic Software or other Electronic Health Record (EHR) platforms.
• Answer aloud, timed: How do you approach integrating custom internal applications with large-scale third-party enterprise systems?

Deliverable: Spoken answers to 2 reported Domain & System Integration question(s), under time.

Day 6 — Answer out loud: Behavioral & Problem-Solving

• Answer aloud, timed: Tell me about yourself and what draws you to software engineering in the healthcare sector.
• Answer aloud, timed: Describe a significant technical challenge you faced in a previous role. How did you identify the root cause, and what steps did you take to solve it?

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

Day 7 — Answer out loud: Technical Fundamentals & Code Quality

• Answer aloud, timed: How do you ensure your code is thoroughly tested before it is deployed to a production environment?
• Answer aloud, timed: Describe your process for conducting a constructive code review for a peer.

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

Behavioural preparation

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

Tell me about your experience working with Epic Software or other Electronic Health Record (EHR) platforms.

Medium · Domain & System Integration

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?

Tell me about yourself and what draws you to software engineering in the healthcare sector.

Medium · Behavioral & Problem-Solving

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?

Tell me about a time when you had to work with a team member who had a different perspective on how to solve a

Medium · Behavioral & Problem-Solving

Tell me about a time when you had to work with a team member who had a different perspective on how to solve a technical problem. How did you reach a resolution?

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 project where requirements changed mid-way through development. How did you adapt your ap

Medium · Behavioral & Problem-Solving

Give an example of a project where requirements changed mid-way through development. How did you adapt your approach?

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 your process for conducting a constructive code review for a peer.

Medium · Technical Fundamentals & Code Quality

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?