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ConnectiveRx Software Engineer Interview Guide

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

The 60-second brief

A Software Engineer at ConnectiveRx plays a vital role in transforming how patients access and afford specialty medications. By developing and optimizing high-performance, secure, and scalable software platforms, you directly impact patient care, helping millions of individuals navigate the complex pharmaceutical landscape. The systems you build power critical services such as copay assistance, patient hub services, and real-time benefit verification, requiring a strong focus on data security, reliability, and transactional integrity. Working in this position means solving complex technical challenges that bridge the gap between healthcare providers, pharmaceutical manufacturers, and patients. You will work on high-throughput APIs, integrations with external healthcare networks, and data-intensive processing pipelines.

This guide is scoped to a Software Engineer candidate at ConnectiveRx.

Focus areas

  • Coding problem solving
  • Data structures
  • Code review skills

The ConnectiveRx interview process

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

Initial Screening Call

A call with a recruiter or hiring manager to evaluate basic technical skills and alignment with the team's needs.

What to demonstrate

  • A call with a recruiter or hiring manager to evaluate basic technical skills and alignment with the team's needs
  • Depth in Coding problem solving

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.

Collaborative Code Review

A session with senior developers to evaluate practical coding abilities and collaborative skills in a team setting.

What to demonstrate

  • A session with senior developers to evaluate practical coding abilities and collaborative skills in a team setting
  • Depth in Coding problem solving

How to prepare

  • Answer aloud and timed: How do you manage memory allocation and garbage collection in your primary programming language when dealing with large datasets?
  • Answer aloud and timed: Walk through an algorithm to detect cycles in a directed graph, and explain its time and space complexity.

Technical and Behavioral Panel

A detailed panel focusing on past projects, complex scenarios, and problem-solving approaches.

What to demonstrate

  • A detailed panel focusing on past projects, complex scenarios, and problem-solving approaches
  • Depth in Coding problem solving

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

Where candidates lose points

Detail your past failures

Do not shy away from discussing projects that did not go as planned. ConnectiveRx interviewers highly value engineers who can analyze past technical failures objectively and explain the concrete preventative measures they implemented as a result.

When walking through your past projects, focus on the "why" behind your technical decisions

Be ready to explain the trade-offs you considered regarding scalability, performance, and development speed.

Brush up on code review best practices

Be prepared to participate in a collaborative code review. Practice reading other people's code, identifying structural issues or logical bugs, and explaining your findings in a professional, constructive manner.

Questions & practice

Given a specific programming language of your choice, how would you optimize a search operation across a highl

Medium · Coding and Data Structures

Given a specific programming language of your choice, how would you optimize a search operation across a highly nested data structure?

Approach

  1. Restate the input: its shape, its size, and what is guaranteed about it.
  2. Name the brute-force solution and its complexity before improving on it.
  3. Choose the data structure from the access pattern, not from familiarity.
  4. State the target complexity and say which constraint rules the naive version out.

Follow-up

  • How does this change if the input no longer fits in memory?
  • What is the worst case, and how likely is it on real data?

Explain the difference between a hash map and a binary search tree, and describe a real-world scenario where y

Medium · Coding and Data Structures

Explain the difference between a hash map and a binary search tree, and describe a real-world scenario where you would choose one over the other.

Approach

  1. Restate the input: its shape, its size, and what is guaranteed about it.
  2. Name the brute-force solution and its complexity before improving on it.
  3. Choose the data structure from the access pattern, not from familiarity.
  4. State the target complexity and say which constraint rules the naive version out.

Follow-up

  • How does this change if the input no longer fits in memory?
  • What is the worst case, and how likely is it on real data?

How do you manage memory allocation and garbage collection in your primary programming language when dealing w

Medium · Coding and Data Structures

How do you manage memory allocation and garbage collection in your primary programming language when dealing with large datasets?

Approach

  1. Say what the runtime actually does before reasoning about the code.
  2. Name what is shared across threads and what owns each piece of state.
  3. Identify the window where an invariant is briefly untrue.
  4. Distinguish a value from a reference to it, and say which one you handed out.

Follow-up

  • What happens if two callers reach this at the same time?
  • Where could this allocate more than you expect?

Walk through an algorithm to detect cycles in a directed graph, and explain its time and space complexity.

Medium · Coding and Data Structures

Approach

  1. Restate the input: its shape, its size, and what is guaranteed about it.
  2. Name the brute-force solution and its complexity before improving on it.
  3. Choose the data structure from the access pattern, not from familiarity.
  4. State the target complexity and say which constraint rules the naive version out.

Follow-up

  • How does this change if the input no longer fits in memory?
  • What is the worst case, and how likely is it on real data?

Explain why the owner filter ignores the listing index

Medium · composite index · query plans · sort elimination

The only index on resource is (tenant_id, status, updated_at DESC, resource_id DESC). A new endpoint returns one user's resources across all statuses, newest created first: WHERE tenant_id = $1 AND owner_user_id = $2 ORDER BY created_at DESC LIMIT 20. On a tenant with 2M rows it takes 900 ms and EXPLAIN shows a sort above a large scan. Explain precisely why the existing index cannot serve it, give the index that can, and state which of these the new index still will not help: owner_user_id alone across tenants; the same query ordered by updated_at. PostgreSQL 16.

Approach

  1. Separate the two jobs an index does. For filtering, a composite btree is seekable only on a left prefix, so with no predicate on status the scan can at best range over tenant_id and test owner_user_id per row; PostgreSQL 16 has no btree skip scan to jump the unconstrained column.
  2. For ordering, the index is sorted by (status, updated_at) within a tenant and not by created_at, so the LIMIT cannot stop early: every matching row is read and then sorted. That is the 'Sort Method: top-N heapsort' line, and it is why the plan reads 2M rows to answer with 20.
  3. Derive the replacement from the access path — equality, equality, then the ordering column: CREATE INDEX CONCURRENTLY ON resource (tenant_id, owner_user_id, created_at DESC). The scan seeks to the (tenant, owner) range and walks 20 entries in order, so the Sort node disappears along with the row-read.
  4. Treat INCLUDE (title, status) as conditional, not free. An index-only scan still visits the heap for any row whose page is not marked all-visible, so on a table taking 1.2k writes/second the win depends on autovacuum keeping the visibility map current, and the wider index costs more on every insert.

Follow-up

  • 90% of rows are status='active'. Would a partial index WHERE status = 'active' change your answer, and for which of the three queries?
  • A dashboard runs this for 40 owners in one page load. What changes about the design?

Stop tag and share joins from fanning out a page

Medium · join fan-out · semi-joins · many-to-many

resource_tag is (resource_id, tag_id) with PK (resource_id, tag_id); resource_share is (resource_id, shared_with_user_id, permission). The tagged-and-shared listing inner-joins resource to both, filters tenant_id, tag_id = ANY($2) and shared_with_user_id = $3, orders by updated_at DESC and takes 50. Pages come back with fewer than 50 distinct resources and the total in the header is far too high. Explain the row multiplication, rewrite both the page query and the count query so each is correct, and name the index each one needs. PostgreSQL 16.

Approach

  1. Do the arithmetic against the predicates that are actually there. An inner join emits one row per matching child row, and both joins are filtered: tag_id = ANY($2) admits only the requested tags, shared_with_user_id = $3 admits one user's share rows. So a resource holding three of the requested tags and shared with $3 once yields three rows, not one — the multiplier is its count of matching tags times its share rows for that single user, and that second factor is 1 unless the table admits duplicate (resource_id, shared_with_user_id) pairs. LIMIT 50 then limits rows rather than resources, and COUNT(*) counts pairs — the header is the product, not the population.
  2. Reject DISTINCT as the fix. It deduplicates after the product has been built, so the planner must materialise and sort the fanned-out set before the LIMIT can apply, and it leaves any SUM or AVG in the same select list wrong.
  3. Rewrite both filters as semi-joins, keeping resource as the only row source: AND EXISTS (SELECT 1 FROM resource_tag rt WHERE rt.resource_id = r.resource_id AND rt.tag_id = ANY($2)) and the same shape against resource_share. A semi-join stops at the first match per resource and preserves the driving index order, so ORDER BY updated_at DESC, resource_id DESC LIMIT 50 still stops after 50 rows.
  4. Count with the same predicates and no join at all: SELECT count(*) FROM resource r WHERE r.tenant_id = $1 AND r.status = 'active' AND EXISTS (...) AND EXISTS (...). Nothing multiplies a resource, so the number is the population.

Follow-up

  • The filter changes from 'any of these tags' to 'all of these tags'. Rewrite it and state what it costs relative to the ANY form.
  • A resource can be shared with the same user twice under different permissions. Does your count change, and should it?

Walk me through your most recent project, detailing your specific roles, responsibilities, and the technical d

Medium · Project Experience & Scenario-Based Ques

Walk me through your most recent project, detailing your specific roles, responsibilities, and the technical decisions you made.

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 complex technical scenario or system failure you faced in a past role. How did you handle it, and w

Medium · Project Experience & Scenario-Based Ques

Describe a complex technical scenario or system failure you faced in a past role. How did you handle it, and what preventative steps did you implement to ensure it would not happen again?

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 approach designing a system that must comply with strict data privacy and security regulations?

Medium · Project Experience & Scenario-Based Ques

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 is your process for reviewing another developer's code to ensure it meets high standards of readability,

Medium · Code Review & Collaboration

What is your process for reviewing another developer's code to ensure it meets high standards of readability, security, and 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?

Describe a situation where you had to explain a complex technical concept to a non-technical stakeholder. How

Medium · Code Review & Collaboration

Describe a situation where you had to explain a complex technical concept to a non-technical stakeholder. How did you structure your communication?

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?

One customer endpoint stalls deliveries to every other destination

Medium · bulkhead · timeouts · saturation

The egress service delivers about 1.5k webhooks/second across 40,000 destinations, with a per-destination concurrency cap of 4 and a 10-second connect-plus-read timeout. Throughput falls to 300/second, queue depth climbs, and p99 delivery latency for unaffected destinations goes from 200 ms to minutes, while the error rate barely moves. One tenant holds 900 destination rows whose URLs share a hostname that now answers in 9.5 seconds. Explain the mechanism with the arithmetic, then give the containment in the order you would apply it.

Approach

  1. Look at saturation before errors. A flat error rate with collapsing throughput says nothing is failing, things are waiting, so the first signal to pull is in-flight request count or pool wait time rather than the error counter. This is the distinction that decides the whole investigation.
  2. Group in-flight work by resolved host, not by destination id. The cap is keyed per destination row, so 900 rows sharing one hostname buy 3,600 concurrent slots against a single host, each held for 9.5 seconds. The bulkhead was never a bulkhead for that host, and grouping by the wrong dimension is why the dashboard looked healthy.
  3. Do the arithmetic in both directions. Required concurrency is arrival rate times latency, so 1.5k/second at 200 ms needs about 300 in flight, which is entirely consumed by 3,600 slow slots; conversely whatever concurrency is left sustains rate equals concurrency divided by 9.5 seconds, which is the 300/second you are seeing. Matching both numbers is what promotes this from a plausible story to the mechanism.
  4. Explain why the circuit breaker never helped. It opens on consecutive failures, and a 9.5-second response inside a 10-second timeout is a success. Slow is not failing, so an error-rate breaker cannot see this; you need a slow-call ratio, a deadline propagated from the caller's remaining budget, or a concurrency limiter.

Follow-up

  • The host recovers to 80 ms. How long does the queue take to drain, and what does the drain do to the recovered host?
  • Where should the 10-second timeout number actually come from?

Suggested practice checklist

Built from the rounds and topics ConnectiveRx candidates report.

Day 1 — Map the ConnectiveRx loop

  • Write out the reported sequence: Initial Screening Call, Collaborative Code Review, Technical and 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 Coding problem solving

  • Spend the session on Coding problem solving, which ConnectiveRx candidates report being tested on.
  • Write one worked example in Coding problem solving and time yourself on it.

Deliverable: One timed worked example in Coding problem solving.

Day 3 — Work Data structures

  • Spend the session on Data structures, which ConnectiveRx candidates report being tested on.
  • Write one worked example in Data structures and time yourself on it.

Deliverable: One timed worked example in Data structures.

Day 4 — Work Code review skills

  • Spend the session on Code review skills, which ConnectiveRx candidates report being tested on.
  • Write one worked example in Code review skills and time yourself on it.

Deliverable: One timed worked example in Code review skills.

Day 5 — Answer out loud: Coding and Data Structures

  • Answer aloud, timed: Given a specific programming language of your choice, how would you optimize a search operation across a highly nested data structure?
  • Answer aloud, timed: Explain the difference between a hash map and a binary search tree, and describe a real-world scenario where you would choose one over the other.

Deliverable: Spoken answers to 2 reported Coding and Data Structures question(s), under time.

Day 6 — Answer out loud: Project Experience & Scenario-Based Questions

  • Answer aloud, timed: Walk me through your most recent project, detailing your specific roles, responsibilities, and the technical decisions you made.
  • Answer aloud, timed: Describe a complex technical scenario or system failure you faced in a past role. How did you handle it, and what preventative steps did you implement to ensure it would not happen again?

Deliverable: Spoken answers to 2 reported Project Experience & Scenario-Based Questions question(s), under time.

Day 7 — Answer out loud: Code Review & Collaboration

  • Answer aloud, timed: How do you handle constructive feedback during a peer code review when you disagree with the reviewer's suggestion?
  • Answer aloud, timed: What is your process for reviewing another developer's code to ensure it meets high standards of readability, security, and performance?

Deliverable: Spoken answers to 2 reported Code Review & Collaboration question(s), under time.

Behavioural preparation

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

Tell me about a time when you had to make a technical trade-off between project delivery speed and long-term c

Medium · Project Experience & Scenario-Based Ques

Tell me about a time when you had to make a technical trade-off between project delivery speed and long-term code quality. What was the outcome?

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 constructive feedback during a peer code review when you disagree with the reviewer's sugges

Medium · Code Review & Collaboration

How do you handle constructive feedback during a peer code review when you disagree with the reviewer's suggestion?

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?

Estimate work you have never done and defend the range

Hard · estimation · backfills · expand-contract

You are asked to estimate a change you have never attempted: add a column to a 100-million-row table, populate it, move reads across, and drop the old shape. Give a range with the assumptions that generate it, including batch size, the signal your backfill throttles on, and wall-clock hours, and name the three unknowns that would move the number most. Then describe a real estimate you gave under comparable ignorance: how you expressed its uncertainty, what you committed to, and how wrong you turned out to be.

Approach

  1. Decompose into independently deployable steps before estimating anything: add the column nullable, write both shapes, backfill in batches, verify, move reads, stop writing the old shape, drop it. That is four deploys spread over days, and the calendar estimate is dominated by them rather than by the loop's runtime.
  2. Do the arithmetic aloud for the part that has arithmetic in it: batch size times number of batches times per-batch duration, at a write rate the primary can absorb alongside roughly 1.2k writes per second of production traffic. The loop is throttled by replication lag and lock waits, not by how fast it can issue statements.
  3. Price the schema step by its lock rather than its statement duration. In PostgreSQL an ALTER TABLE taking ACCESS EXCLUSIVE waits for every open transaction on that table while later queries queue behind it, so a millisecond change issued during a thirty-second analytics query stalls that table for thirty seconds. Adding a nullable column with a non-volatile default avoids a rewrite from version 11; a new index wants CREATE INDEX CONCURRENTLY, which cannot run inside a transaction block and leaves an invalid index behind if it fails.
  4. Express the answer as a range whose endpoints each trace to a stated assumption, then name the cheapest experiment that collapses it, which is almost always running one real batch against the real table and multiplying.

Follow-up

  • How do you verify the backfill genuinely finished, given rows written by production traffic while it ran?
  • Where does the backfill resume from after a worker is killed mid-batch, and what makes that resume point trustworthy?