cswork / libraryOpen practice workspace

Interview guides · Community Health Network (Indiana)

Community Health Network (Indiana) Software Engineer Interview Guide

Community Health Network (Indiana) Software Engineer interview guide: reported rounds, questions and how candidates describe the process.

The 60-second brief

As a Software Engineer at Community Health Network (Indiana), you are at the critical intersection of healthcare delivery and enterprise technology. Your work directly impacts the daily operations of clinicians, administrative staff, and ultimately, the patients who rely on our network for care. This role is not just about writing code; it is about building, integrating, and maintaining the secure, scalable systems that keep a modern healthcare network running smoothly. Because our infrastructure heavily leverages enterprise tools, this position frequently overlaps with systems engineering—specifically within the Microsoft 365 ecosystem. You will be responsible for designing integrations, automating workflows, and ensuring that our communication and productivity platforms are highly available and secure.

This guide is scoped to a Software Engineer candidate at Community Health Network (Indiana).

Focus areas

  • Microsoft 365
  • Behavioral Interviewing
  • Systems Engineering (Sr Systems Engineer)

The Community Health Network (Indiana) interview process

Community Health Network (Indiana) candidates report 3 rounds over 3-5 weeks. The stages below are what candidates describe, not a published process.

Recruiter Screen

Initial screening focused on your background and overall fit for the role.

What to demonstrate

  • Initial screening focused on your background and overall fit for the role
  • Depth in Microsoft 365

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

Conversations with two different managers discussing past projects and technical depth.

What to demonstrate

  • Conversations with two different managers discussing past projects and technical depth
  • Depth in Microsoft 365

How to prepare

  • Answer aloud and timed: Give an example of a project that required you to learn a completely new domain or business process quickly.
  • Answer aloud and timed: Tell me about a time you noticed a process was broken and took the initiative to fix it without being asked.

Behavioral Panel

Extensive face-to-face or virtual panel with peers from different departments assessing collaboration and cultural fit.

What to demonstrate

  • Extensive face-to-face or virtual panel with peers from different departments assessing collaboration and cultural fit
  • Depth in Microsoft 365

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 panel above and write down what you would ask to confirm before it.

Where candidates lose points

Master the STAR Method

With six or more behavioral questions in the final round, your answers must be structured and concise. Always clearly define the Situation, the Task at hand, the specific Actions you took, and the measurable Results.

Prepare for the Peer Panel

Remember that your final interview includes peers from outside your department. Avoid overly dense technical jargon when answering behavioral questions; focus on business impact, teamwork, and communication.

The final round peer panel is highly unique

Treat these interviewers with the same level of respect and thoroughness as you would a hiring manager. They have significant veto power regarding your cultural fit.

Highlight Automation

In any systems or software engineering role here, efficiency is key. Whenever possible, steer your technical answers toward how you have used scripting or software to eliminate manual toil.

Questions & practice

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?

Canonicalise a request body into a stable idempotency fingerprint

Medium · parsing · canonicalisation · hashing

idempotency_key.request_fingerprint is a SHA-256 over the method, path and canonicalised body, and a retry whose fingerprint differs must be rejected with 422 rather than served the stored response. Write the canonicaliser. Bodies are JSON up to 256 KB nested at most 32 levels; clients vary key order, whitespace and unicode escaping, and some send 64-bit ids as JSON numbers. Produce a deterministic byte string such that semantically identical bodies match and any semantic difference does not. State your complexity and name two normalisations you refuse to perform.

Approach

  1. Parse once into a tree, then re-serialise under fixed rules: object keys sorted, array order preserved, one escaping convention, no insignificant whitespace. Parsing is O(n) and sorting keys is O(k log k) per object, so O(n log n) overall with O(depth) stack, and the 32-level cap is enforced during parsing because hostile nesting is how a canonicaliser becomes a stack overflow.
  2. Sort keys by their UTF-8 bytes and say why the obvious implementation is wrong in some runtimes: a default string comparison that orders by UTF-16 code units places surrogate pairs, meaning code points from U+10000 up, below U+E000 to U+FFFF, which is not UTF-8 byte order, so two services written in different languages disagree on the same document.
  3. Do not re-encode numbers through a double. IEEE-754 binary64 represents integers exactly only up to 2^53, so normalising a 19-digit id through a float changes it, and 1 against 1.0 cannot be reconciled without deciding whether they are the same value. Preserve the literal token, and require ids as strings at the API boundary if you want them comparable.
  4. Reject duplicate keys rather than picking one. JSON permits them and parsers disagree, most keeping the last, so any choice you make ties the fingerprint to a parser detail that the code handling the request does not necessarily share.

Follow-up

  • A client sends the same logical request with an extra field your API ignores. Same key, different fingerprint, so you return 422. Is that the right answer?
  • Where does the fingerprint get computed relative to request decompression and the body-size limit?

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?

Hold a per-tenant active cap against concurrent creates

Hard · write skew · isolation levels · constraints

A tenant on the standard plan may hold at most 50 resources with status='active'. The create handler runs SELECT count(*) FROM resource WHERE tenant_id = $1 AND status = 'active', compares to 50, then inserts. Two creates arrive 3 ms apart on different instances and the tenant lands at 51. Name the anomaly, say whether PostgreSQL 16 READ COMMITTED or REPEATABLE READ prevents it and why, then give an implementation that holds the cap at READ COMMITTED with the exact statements. Finally, say what changes when the cap is 'at most one running export per tenant' on job_run.

Approach

  1. Name it: write skew. The two transactions read an overlapping set and write disjoint rows, so there is no row-level conflict for the engine to detect and each commit is individually legal.
  2. Rule out the levels precisely. READ COMMITTED takes a fresh snapshot per statement and takes no lock on the counted rows, so both see 49. PostgreSQL's REPEATABLE READ is snapshot isolation: it removes non-repeatable reads and phantoms within the snapshot but still admits write skew, because the anomaly is not a re-read of a changed row, it is a read of a set that a concurrent transaction invalidates. Only SERIALIZABLE closes it, by tracking the read dependency and aborting one transaction with SQLSTATE 40001 — a guarantee that exists only if the application re-runs the whole transaction from the read.
  3. Convert the set predicate into a single-row conflict: keep tenant.active_resource_count and run UPDATE tenant SET active_resource_count = active_resource_count + 1 WHERE tenant_id = $1 AND active_resource_count < 50 in the same transaction as the INSERT. Zero affected rows is the cap, returned as 409. The row lock serialises the decision at any isolation level, and contention is bounded to one tenant's row — which is also the fair-scheduling unit, unlike a global counter that would convoy every tenant behind one row.
  4. State the cost you just took on: a counter is a second source of truth that can drift, so every path that changes status must adjust it inside the same transaction, and a periodic reconciliation has to exist, with resource_revision as the authority for what the count should have been.

Follow-up

  • A resource moves from archived back to active. Which statements change, and what breaks if the counter update and the status change land in different transactions?
  • The cap becomes plan-dependent and a plan can change mid-month. Where does the number 50 live, and who reads it?

Keep soft-deleted accounts from blocking re-registration

Easy · soft delete · unique constraints · engine differences

app_user holds user_id, tenant_id, email CITEXT, password_hash (NULL for SSO principals), email_verified_at, auth_version, status ('invited','active','suspended','deactivated'), created_at, updated_at, deleted_at. Two live accounts for one address inside a tenant must be impossible, but an address freed by a soft delete must be reusable, and the same tenant may delete and re-register it repeatedly. Write the uniqueness DDL for PostgreSQL 16, then the equivalent for MySQL 8 where partial indexes do not exist, and say what each permits once three deleted rows already hold that address.

Approach

  1. Start from what is actually unique: not (tenant_id, email), but (tenant_id, email) among live rows. PostgreSQL says that directly — CREATE UNIQUE INDEX app_user_live_email ON app_user (tenant_id, email) WHERE deleted_at IS NULL. A full constraint over the same two columns burns the address permanently the first time someone deletes an account.
  2. Keep case-insensitivity in the type or the index, never in the application: CITEXT as given, or UNIQUE (tenant_id, lower(email)) as an expression index where the extension is unavailable. A case-sensitive unique column is exactly how two accounts for one human appear.
  3. For MySQL 8 the predicate has to move inside the key: add a discriminator column that is a constant 0 while the row is live and is set to user_id on delete, with UNIQUE (tenant_id, email, deleted_marker). Live rows share the constant and still collide; deleted rows differ from each other and stop colliding.
  4. State the NULL variant and its dependency: leaving the marker NULL for deleted rows also works, because a unique index treats NULLs as distinct — true in MySQL, and true in PostgreSQL only under the default NULLS DISTINCT, which PostgreSQL 15 lets you reverse. Check the polarity against the three existing deleted rows: constant-on-live is what preserves the collision you want, and reversing it silently admits duplicate live accounts.

Follow-up

  • A deleted account re-registers with the same address the next day. Do the old resource rows follow the new user_id, and how does the API keep the two principals apart?
  • How do you honour an erasure request while resource_revision.actor_user_id still references this table?

How do you approach securing a Microsoft 365 environment against external threats while maintaining user conve

Medium · Systems Engineering and Microsoft 365

How do you approach securing a Microsoft 365 environment against external threats while maintaining user convenience?

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 complex PowerShell script you wrote. What problem did it solve, and how did you ensure it wa

Medium · Systems Engineering and Microsoft 365

Walk us through a complex PowerShell script you wrote. What problem did it solve, and how did you ensure it was error-proof?

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?

Explain how you would design an automated onboarding and offboarding process for employees across multiple ent

Medium · Systems Engineering and Microsoft 365

Explain how you would design an automated onboarding and offboarding process for employees across multiple enterprise systems.

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 your experience with Microsoft Graph API. How have you used it to integrate custom software with M365

Medium · Systems Engineering and Microsoft 365

Describe your experience with Microsoft Graph API. How have you used it to integrate custom software with M365?

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?

If a critical enterprise application suddenly stopped communicating with our identity provider, how would you

Medium · Problem-Solving and Troubleshooting

If a critical enterprise application suddenly stopped communicating with our identity provider, how would you begin troubleshooting?

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 Community Health Network (Indiana) candidates report.

Day 1 — Map the Community Health Network (Indiana) loop

  • Write out the reported sequence: Recruiter Screen, Technical Interviews, Behavioral 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 Microsoft 365

  • Spend the session on Microsoft 365, which Community Health Network (Indiana) candidates report being tested on.
  • Write one worked example in Microsoft 365 and time yourself on it.

Deliverable: One timed worked example in Microsoft 365.

Day 3 — Work Behavioral Interviewing

  • Spend the session on Behavioral Interviewing, which Community Health Network (Indiana) candidates report being tested on.
  • Write one worked example in Behavioral Interviewing and time yourself on it.

Deliverable: One timed worked example in Behavioral Interviewing.

Day 4 — Work Systems Engineering (Sr Systems Engineer)

  • Spend the session on Systems Engineering (Sr Systems Engineer), which Community Health Network (Indiana) candidates report being tested on.
  • Write one worked example in Systems Engineering (Sr Systems Engineer) and time yourself on it.

Deliverable: One timed worked example in Systems Engineering (Sr Systems Engineer).

Day 5 — Answer out loud: Behavioral and Cross-Functional Collaboration

  • Answer aloud, timed: Tell me about a time you had to work with a difficult stakeholder from another department. How did you build trust?
  • Answer aloud, timed: Describe a time when you received constructive criticism from a peer. How did you react, and what changes did you make?

Deliverable: Spoken answers to 2 reported Behavioral and Cross-Functional Collaboration question(s), under time.

Day 6 — Answer out loud: Systems Engineering and Microsoft 365

  • Answer aloud, timed: How do you approach securing a Microsoft 365 environment against external threats while maintaining user convenience?
  • Answer aloud, timed: Walk us through a complex PowerShell script you wrote. What problem did it solve, and how did you ensure it was error-proof?

Deliverable: Spoken answers to 2 reported Systems Engineering and Microsoft 365 question(s), under time.

Day 7 — Answer out loud: Problem-Solving and Troubleshooting

  • Answer aloud, timed: Tell me about the most challenging technical issue you have ever debugged. What was your step-by-step process?
  • Answer aloud, timed: If a critical enterprise application suddenly stopped communicating with our identity provider, how would you begin troubleshooting?

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

Behavioural preparation

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

Tell me about a time you had to work with a difficult stakeholder from another department. How did you build t

Medium · Behavioral and Cross-Functional Collabor

Tell me about a time you had to work with a difficult stakeholder from another department. How did you build trust?

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 received constructive criticism from a peer. How did you react, and what changes did

Medium · Behavioral and Cross-Functional Collabor

Describe a time when you received constructive criticism from a peer. How did you react, and what changes did you make?

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 that required you to learn a completely new domain or business process quickly.

Medium · Behavioral and Cross-Functional Collabor

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 noticed a process was broken and took the initiative to fix it without being asked.

Medium · Behavioral and Cross-Functional Collabor

Approach

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

Follow-up

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

Describe a situation where you had to balance multiple urgent requests from different teams. How did you prior

Medium · Behavioral and Cross-Functional Collabor

Describe a situation where you had to balance multiple urgent requests from different teams. How did you prioritize?

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 the most challenging technical issue you have ever debugged. What was your step-by-step process?

Medium · Problem-Solving and Troubleshooting

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 a deployment went wrong. How did you handle the immediate fallout, and what did you learn

Medium · Problem-Solving and Troubleshooting

Describe a time when a deployment went wrong. How did you handle the immediate fallout, and what did you learn?

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?