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Press ganey Software Engineer Interview Guide

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

The 60-second brief

A Software Engineer at Press Ganey plays a vital role in shaping the technology that powers the healthcare industry's leading patient experience and workforce engagement platforms. By developing high-performance, secure, and scalable software, you directly contribute to products that collect and analyze millions of patient touchpoints daily. The insights generated by your code help hospitals, health systems, and medical practices across the United States improve clinical quality, safety, and patient care. In this role, you will work on mission-critical applications that handle large-scale data ingestion, complex analytics, and highly secure reporting dashboards. Because Press Ganey deals with sensitive healthcare information, your work will involve building robust, compliant architectures using modern backend systems, cloud technologies, and relational databases.

This guide is scoped to a Software Engineer candidate at Press ganey.

Focus areas

  • Java
  • REST APIs
  • Spring Boot

The Press ganey interview process

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

Recruiter Screen

Brief discussion about your background and high-level alignment with the role.

What to demonstrate

  • Brief discussion about your background and high-level alignment with the role
  • Depth in Java

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 Screening

May involve a video interview with a hiring manager or a take-home coding exercise.

What to demonstrate

  • May involve a video interview with a hiring manager or a take-home coding exercise
  • Depth in Java

How to prepare

  • Answer aloud and timed: How does dependency injection work in Spring Boot, and what are the benefits of using it in a microservices environment?
  • Answer aloud and timed: Describe the lifecycle of a request in a Spring Boot application from the controller layer to the database.

Technical Panel Interviews

Deeper technical interviews with senior engineers and department management.

What to demonstrate

  • Deeper technical interviews with senior engineers and department management
  • Depth in Java

How to prepare

  • Answer aloud and timed: How do you handle asynchronous processing and REST API callbacks in a multi-threaded Java application?
  • Answer aloud and timed: Write a complex MySQL query that involves multiple joins, aggregations, and subqueries, and explain how you would optimize its execution plan.

Behavioral Assessments

Assessments focused on behavioral fit with the team and company culture.

What to demonstrate

  • Assessments focused on behavioral fit with the team and company culture
  • Depth in Java

How to prepare

  • Prepare three examples from your own work, each with a decision you made and an outcome you can quantify.
  • Re-read the description of the behavioral assessments above and write down what you would ask to confirm before it.

Where candidates lose points

Showcase Clean Coding Standards

During coding reviews or take-home exercises, prioritize readability, proper naming conventions, and modular design. The team values code that is easy for others to read and maintain.

Brush Up on SQL

Do not neglect database questions. Be ready to write raw SQL queries, explain joins, and discuss how you would optimize database performance under heavy load.

Communicate Your Process

When answering technical or system design questions, walk the interviewer through your thought process. Explain the trade-offs of different approaches and why you prefer one solution over another.

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?

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?

Archive a resource graph without breaking live references or recursing

Medium · graph traversal · topological order · tenant isolation

Resources reference other resources within a tenant; for the largest tenant the reference table holds up to 2,000,000 nodes and 8,000,000 edges. Archiving a resource must archive everything reachable from it that nothing outside the set still references, refuse when a live external referrer exists, and terminate when references form cycles, which they legitimately do. Produce the archive order and the refusal list, targeting O(V+E). Say what stops the traversal crossing a tenant boundary, and why recursion is the wrong control structure at this size.

Approach

  1. Load the subgraph with the tenant predicate on both endpoints of the edge, not only on the side you started from. Scoping the left table alone is the classic cross-tenant leak: one mis-entered edge then pulls another tenant's resources into the traversal and, worse, into the archive.
  2. Traverse iteratively with an explicit stack. A 2,000,000-node graph can hold a chain deep enough to exhaust a native stack in the low tens of thousands of frames, and that failure is a process crash rather than an error you can return.
  3. Treat cycles as data rather than corruption: compute strongly connected components with Tarjan in O(V+E) using its own explicit stack, then condense. The condensation is a DAG, so a topological order over it gives the archive order, and every member of a component archives in one transaction because no order within a cycle is valid.
  4. Decide refusals with reverse edges. A candidate is archivable only if every in-edge originates inside the candidate set, so build the transpose or count in-degrees restricted to the visited set, and emit each blocked resource with the id of the external referrer, which is the only part of the answer an operator can act on.

Follow-up

  • The graph is read in one query and the archive writes a minute later. What can change in between, and how do you make the write safe?
  • The candidate set is 400,000 resources. Is that one transaction, and if not, what does a half-finished archive look like to a reader?

Write a complex MySQL query that involves multiple joins, aggregations, and subqueries, and explain how you wo

Medium · Database & System Design

Write a complex MySQL query that involves multiple joins, aggregations, and subqueries, and explain how you would optimize its execution plan.

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?

Explain the concept of database indexing. When would you use a composite index versus a single-column index?

Medium · Database & System Design

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?

Explain the JVM architecture and how garbage collection works under the hood.

Medium · Java & Backend Technology

Approach

  1. Fix the scope first: who calls this, how often, and what they do when it fails.
  2. Name the read and write paths separately; they rarely have the same bottleneck.
  3. Choose a partition key and say what query it makes expensive.
  4. 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 are the major differences between Java 8 features (like Streams and Lambdas) and older Java versions? How

Medium · Java & Backend Technology

What are the major differences between Java 8 features (like Streams and Lambdas) and older Java versions? How do they improve performance?

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 does dependency injection work in Spring Boot, and what are the benefits of using it in a microservices en

Medium · Java & Backend Technology

How does dependency injection work in Spring Boot, and what are the benefits of using it in a microservices environment?

Approach

  1. Fix the scope first: who calls this, how often, and what they do when it fails.
  2. Name the read and write paths separately; they rarely have the same bottleneck.
  3. Choose a partition key and say what query it makes expensive.
  4. 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?

Describe the lifecycle of a request in a Spring Boot application from the controller layer to the database.

Medium · Java & Backend Technology

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 handle asynchronous processing and REST API callbacks in a multi-threaded Java application?

Medium · Java & Backend Technology

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 design a database schema that supports high-throughput write operations while maintaining data inte

Medium · Database & System Design

How do you design a database schema that supports high-throughput write operations while maintaining data integrity?

Approach

  1. Fix the scope first: who calls this, how often, and what they do when it fails.
  2. Name the read and write paths separately; they rarely have the same bottleneck.
  3. Choose a partition key and say what query it makes expensive.
  4. 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?

Describe a scenario where you had to refactor a slow-performing API endpoint. What was your approach to diagno

Medium · Database & System Design

Describe a scenario where you had to refactor a slow-performing API endpoint. What was your approach to diagnosing and fixing the bottleneck?

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?

One log partition stops advancing while the others drain

Easy · poison message · head-of-line blocking · consumer lag

Search results for a subset of tenants are hours stale; the rest are current. The projection consumer reports lag of zero on 15 of 16 partitions and 400,000 on one. Its error rate is flat and its CPU is idle. outbox_event has no pending rows older than a second, so the relay has published everything it holds. Identify the mechanism, give the ordered checks, and state what you do in the first ten minutes versus what you change permanently.

Approach

  1. Read the lag distribution first. A slow consumer lags everywhere; zero on fifteen partitions and 400,000 on one is not throughput. Idle CPU on the stuck partition means the consumer is not advancing its offset at all, which points at one message it cannot get past rather than at a rate problem.
  2. Exonerate the producer before touching the consumer. No pending outbox rows older than a second means the relay published, so the event exists in the log. This separates never sent from sent and never applied, which are different code paths and usually different owners.
  3. Read the message at the stuck offset and the handler's log lines for its event_id. A flat error rate with no progress has two explanations and you must distinguish them: the handler is throwing and the retry loop is swallowing it, or the handler is blocking on something and never returning. Idle CPU with no error lines favours the second.
  4. Mitigate before diagnosing further. Move the offending event to a dead-letter store and commit the offset past it. Adding consumers does nothing here, because a partition is consumed by exactly one member of the group, and the blast radius is every aggregate hashed to that partition, not only the aggregate that produced the bad event.

Follow-up

  • The dead-lettered event carried aggregate_version 7 and the projection had applied 6. What must the replay do differently if 8 and 9 landed in the meantime?
  • How do you show staleness to the user while the partition is behind, given the API already returns the projection's watermark?

Suggested practice checklist

Built from the rounds and topics Press ganey candidates report.

Day 1 — Map the Press ganey loop

  • Write out the reported sequence: Recruiter Screen, Technical Screening, Technical Panel Interviews, Behavioral Assessments.
  • 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 Java

  • Spend the session on Java, which Press ganey candidates report being tested on.
  • Write one worked example in Java and time yourself on it.

Deliverable: One timed worked example in Java.

Day 3 — Work REST APIs

  • Spend the session on REST APIs, which Press ganey candidates report being tested on.
  • Write one worked example in REST APIs and time yourself on it.

Deliverable: One timed worked example in REST APIs.

Day 4 — Work Spring Boot

  • Spend the session on Spring Boot, which Press ganey candidates report being tested on.
  • Write one worked example in Spring Boot and time yourself on it.

Deliverable: One timed worked example in Spring Boot.

Day 5 — Answer out loud: Java & Backend Technology

  • Answer aloud, timed: Explain the JVM architecture and how garbage collection works under the hood.
  • Answer aloud, timed: What are the major differences between Java 8 features (like Streams and Lambdas) and older Java versions? How do they improve performance?

Deliverable: Spoken answers to 2 reported Java & Backend Technology question(s), under time.

Day 6 — Answer out loud: Database & System Design

  • Answer aloud, timed: Write a complex MySQL query that involves multiple joins, aggregations, and subqueries, and explain how you would optimize its execution plan.
  • Answer aloud, timed: How do you design a database schema that supports high-throughput write operations while maintaining data integrity?

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

Day 7 — Answer out loud: Behavioral & Project Discussion

  • Answer aloud, timed: Walk me through a complex software engineering project you recently led or contributed to. What were your specific roles and responsibilities?
  • Answer aloud, timed: Describe a time when you disagreed with a technical decision made by a peer or manager. How did you handle the situation and reach a resolution?

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

Behavioural preparation

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

How do you handle database transaction management and prevent race conditions in a distributed system?

Medium · Database & System Design

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?

Walk me through a complex software engineering project you recently led or contributed to. What were your spec

Medium · Behavioral & Project Discussion

Walk me through a complex software engineering project you recently led or contributed to. What were your specific roles and responsibilities?

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 time when you disagreed with a technical decision made by a peer or manager. How did you handle the

Medium · Behavioral & Project Discussion

Describe a time when you disagreed with a technical decision made by a peer or manager. How did you handle the situation and 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?

How do you prioritize your tasks when working on a project with tight deadlines and shifting requirements?

Medium · Behavioral & Project Discussion

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 you had to learn a new technology quickly to solve a production issue or deliver a featur

Medium · Behavioral & Project Discussion

Tell me about a time you had to learn a new technology quickly to solve a production issue or deliver a feature.

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 ensure code quality and maintainability within your team? What is your approach to conducting const

Medium · Behavioral & Project Discussion

How do you ensure code quality and maintainability within your team? What is your approach to conducting constructive code reviews?

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?