At Northmarq, a Software Engineer plays a pivotal role in driving the technology that powers one of the nation's leading commercial real estate investment banking and finance firms. Operating primarily within the Salesforce ecosystem, this role is highly focused on developing, customizing, and scaling the platforms that support debt, equity, investment sales, and loan servicing. You will not just write code; you will design the digital infrastructure that enables brokers, analysts, and financial producers to execute multi-million dollar transactions seamlessly. The impact of this position is substantial. By building robust integrations, streamlining complex workflows, and deploying customized lightning web components, you directly influence the efficiency of Northmarq’s transaction pipeline. The engineering team focuses on transforming legacy financial workflows into modern, automated systems, making your work highly visible and strategically vital to the company's overall growth. For engineers who enjoy seeing the direct business impact of their code, this environment offers a unique challenge. You will navigate the complexities of commercial real estate data models, integrate proprietary financial tools with Salesforce, and collaborate closely with business stakeholders to build tools that define how the company operates on a daily basis.
Phone Screening
reportedInitial 30-minute conversation with a recruiter focusing on background, qualifications, and career aspirations.
What to demonstrate
- Initial 30-minute conversation with a recruiter focusing on background, qualifications, and career aspirations
- Depth in Salesforce (CRM Platform)
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 and Behavioral Interview
reportedCollaborative session with the hiring manager centered around past project work and technical decision-making.
What to demonstrate
- Collaborative session with the hiring manager centered around past project work and technical decision-making
- Depth in Salesforce (CRM Platform)
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 interview above and write down what you would ask to confirm before it.
PracHub editorial advice for the preparation topics above.
Focus on your project stories
When discussing your background, use the STAR method (Situation, Task, Action, Result) to explain your past projects. Be highly specific about your individual contributions and the technical decisions you made.
Showcase your business acumen
Northmarq is a business-driven organization. Whenever you explain a technical solution, tie it back to the business outcome, such as time saved for brokers, increased data accuracy, or automated financial workflows.
Answering a debugging question with a guess instead of a bisection
Give a procedure that halves the search space at each step: confirm the symptom reproduces, establish the last known-good version, input or timestamp, then bisect over commits, over the data, or over the layers of the request path. A plausible cause with no way to confirm it is the same move whether it happens to be right or wrong, which is why it scores nothing.
Choose a category, try a prompt, then open its approach, worked solution or follow-up when you need it.
Archive a resource graph without breaking live references or recursing
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
- 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.
- 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.
- 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.
- 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?
Identify the heaviest tenants in a five-minute window under memory pressure
The edge service handles about 3,000 requests per second across roughly 50,000 tenants, peaking near 9,000. Expose the 50 heaviest tenants by request count over the trailing five minutes so limits can be tightened before one tenant's backfill starves the fleet. You may not retain five minutes of raw records. Give the exact solution and its memory, then the bounded-memory approximation with its error stated as a formula, and say which you would ship and at what tenant cardinality that choice changes.
Approach
- Do the exact version first, because it is affordable at this cardinality: a ring of 300 one-second counters per tenant, advanced lazily, is 1,200 bytes of counters per tenant and roughly 60 to 90 MB for 50,000 tenants with overhead. Carry a running total and subtract the bucket you overwrite so a window read is O(1) rather than 300 adds.
- Extract the top 50 with a size-k min-heap over the tenant sums: O(d log k) for d tenants, against O(d log d) to sort them all. Maintaining the heap continuously instead of on query requires a tenant-to-heap-index map, because incrementing a count already inside the heap means sifting from a known position, and without that map you rebuild the heap on every request.
- State the approximation precisely rather than gesturing at sketches. Misra-Gries with m counters retains every item whose true count exceeds N/(m+1), and each retained count underestimates the truth by at most N/(m+1). With m = 1,000 and N = 900,000 requests in the window the error is roughly 900 requests, which is fine for spotting a tenant sending 50,000 and useless for ranking two tenants 200 apart.
- Say what breaks when the window slides: Misra-Gries and Space-Saving are insert-only and cannot be decremented as records age out. The workable construction is one summary per sub-window, say ten seconds, with 30 summaries merged at query time, and the merged error is the sum of the per-summary errors, so the bound degrades linearly in the number of sub-windows.
Follow-up
- The heaviest tenant is heavy because of one export job rather than user traffic. Should the limiter treat those as the same tenant?
- Two tenants sit tied at the boundary of the top 50. Does your answer flap, and does the flapping matter?
Canonicalise a request body into a stable idempotency fingerprint
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
- 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.
- 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.
- 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.
- 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?
Hold a per-tenant active cap against concurrent creates
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
- 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.
- 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.
- 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.
- 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
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
- 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.
- 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.
- 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.
- 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 decide between using Apex code versus native Salesforce declarative tools like Flows?
How do you decide between using Apex code versus native Salesforce declarative tools like Flows?
Approach
- Clarify what is being asked and what a complete answer contains.
- State your assumptions explicitly before working the problem.
- Say what you would check first and why it is the highest-information step.
- Work from the requirement backwards to the design.
Follow-up
- What assumption would you test first?
- How would you know your answer was wrong?
Can you explain the lifecycle of a trigger and how you ensure triggers remain performant under high data volum
Can you explain the lifecycle of a trigger and how you ensure triggers remain performant under high data volumes?
Approach
- Clarify what is being asked and what a complete answer contains.
- State your assumptions explicitly before working the problem.
- Say what you would check first and why it is the highest-information step.
- 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 enforce data security and sharing rules within custom-developed modules?
What strategies do you use to enforce data security and sharing rules within custom-developed modules?
Approach
- Clarify what is being asked and what a complete answer contains.
- State your assumptions explicitly before working the problem.
- Say what you would check first and why it is the highest-information step.
- 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 me through a challenging project you recently completed. What was your specific contribution, and what te
Walk me through a challenging project you recently completed. What was your specific contribution, and what technical trade-offs did you make?
Approach
- Fix the scope first: who calls this, how often, and what they do when it fails.
- Name the read and write paths separately; they rarely have the same bottleneck.
- Choose a partition key and say what query it makes expensive.
- 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?
How do you design a custom data model in Salesforce to support a complex business workflow with multiple paren
How do you design a custom data model in Salesforce to support a complex business workflow with multiple parent-child relationships?
Approach
- Fix the scope first: who calls this, how often, and what they do when it fails.
- Name the read and write paths separately; they rarely have the same bottleneck.
- Choose a partition key and say what query it makes expensive.
- 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?
How do you approach testing and deployment in a multi-sandbox environment to ensure zero downtime for active b
How do you approach testing and deployment in a multi-sandbox environment to ensure zero downtime for active business users?
Approach
- Fix the scope first: who calls this, how often, and what they do when it fails.
- Name the read and write paths separately; they rarely have the same bottleneck.
- Choose a partition key and say what query it makes expensive.
- 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?
One log partition stops advancing while the others drain
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
- 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.
- 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.
- 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.
- 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?
Built from the rounds and topics Northmarq candidates report.
Prepare, practise & reflect
One practical outcome each day. Spend longer where you need it.
0 / 7 done01Map the Northmarq loop
- Write out the reported sequence: Phone Screening, Technical and Behavioral Interview.
- For each round, write one sentence on what it is judging, from the description above, and mark the one you are least ready for.
Deliverable: A one-page map of the 2 reported rounds, with the weakest marked.
02Work Salesforce (CRM Platform)
- Spend the session on Salesforce (CRM Platform), which Northmarq candidates report being tested on.
- Write one worked example in Salesforce (CRM Platform) and time yourself on it.
Deliverable: One timed worked example in Salesforce (CRM Platform).
03Work Salesforce Development
- Spend the session on Salesforce Development, which Northmarq candidates report being tested on.
- Write one worked example in Salesforce Development and time yourself on it.
Deliverable: One timed worked example in Salesforce Development.
04Work Software Engineering (General)
- Spend the session on Software Engineering (General), which Northmarq candidates report being tested on.
- Write one worked example in Software Engineering (General) and time yourself on it.
Deliverable: One timed worked example in Software Engineering (General).
05Answer out loud: Salesforce & Technical Execution
- Answer aloud, timed: How do you decide between using Apex code versus native Salesforce declarative tools like Flows?
- Answer aloud, timed: Can you explain the lifecycle of a trigger and how you ensure triggers remain performant under high data volumes?
Deliverable: Spoken answers to 2 reported Salesforce & Technical Execution question(s), under time.
06Answer out loud: Project Walkthroughs & Architecture
- Answer aloud, timed: Walk me through a challenging project you recently completed. What was your specific contribution, and what technical trade-offs did you make?
- Answer aloud, timed: How do you design a custom data model in Salesforce to support a complex business workflow with multiple parent-child relationships?
Deliverable: Spoken answers to 2 reported Project Walkthroughs & Architecture question(s), under time.
07Answer out loud: Behavioral & Aspirations
- Answer aloud, timed: Why are you interested in joining Northmarq as a Software Engineer, and how does this role align with your long-term career aspirations?
- Answer aloud, timed: Describe a situation where you had to work with a stakeholder who did not understand technical limitations. How did you manage their expectations?
Deliverable: Spoken answers to 2 reported Behavioral & Aspirations question(s), under time.
Expand any day for tasks and deliverables. Your progress is saved on this device.
Behavioural rounds judge the decision you made and what it cost.
Describe your experience building custom Lightning Web Components (LWC) and how you manage state and communica
Describe your experience building custom Lightning Web Components (LWC) and how you manage state and communication between components.
Approach
- Pick a story where you made the decision, not one where you watched it.
- State the situation in two sentences and spend the rest on the reasoning.
- Give the blast radius: what could have broken, and what you measured.
- 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 integration challenges when connecting Salesforce with external financial APIs or proprietar
How do you handle integration challenges when connecting Salesforce with external financial APIs or proprietary databases?
Approach
- Pick a story where you made the decision, not one where you watched it.
- State the situation in two sentences and spend the rest on the reasoning.
- Give the blast radius: what could have broken, and what you measured.
- 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 had to optimize a slow-running query or resolve a governor limit issue in Apex.
Describe a time when you had to optimize a slow-running query or resolve a governor limit issue in Apex.
Approach
- Pick a story where you made the decision, not one where you watched it.
- State the situation in two sentences and spend the rest on the reasoning.
- Give the blast radius: what could have broken, and what you measured.
- 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?
Why are you interested in joining Northmarq as a Software Engineer, and how does this role align with your lon
Why are you interested in joining Northmarq as a Software Engineer, and how does this role align with your long-term career aspirations?
Approach
- Pick a story where you made the decision, not one where you watched it.
- State the situation in two sentences and spend the rest on the reasoning.
- Give the blast radius: what could have broken, and what you measured.
- 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 work with a stakeholder who did not understand technical limitations. Ho
Describe a situation where you had to work with a stakeholder who did not understand technical limitations. How did you manage their expectations?
Approach
- Pick a story where you made the decision, not one where you watched it.
- State the situation in two sentences and spend the rest on the reasoning.
- Give the blast radius: what could have broken, and what you measured.
- 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 made a mistake on a project. How did you identify it, and what did you do to rectify
Tell me about a time you made a mistake on a project. How did you identify it, and what did you do to rectify the situation?
Approach
- Pick a story where you made the decision, not one where you watched it.
- State the situation in two sentences and spend the rest on the reasoning.
- Give the blast radius: what could have broken, and what you measured.
- 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 keep up with the tri-annual Salesforce release cycles and decide which new features to implement?
How do you keep up with the tri-annual Salesforce release cycles and decide which new features to implement?
Approach
- Pick a story where you made the decision, not one where you watched it.
- State the situation in two sentences and spend the rest on the reasoning.
- Give the blast radius: what could have broken, and what you measured.
- 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?
- 01
Describe your experience building custom Lightning Web Components (LWC) and how you manage state and communication between components.
- 02
How do you handle integration challenges when connecting Salesforce with external financial APIs or proprietary databases?
- 03
Describe a time when you had to optimize a slow-running query or resolve a governor limit issue in Apex.
- 04
Why are you interested in joining Northmarq as a Software Engineer, and how does this role align with your long-term career aspirations?
What is the primary focus of the Software Engineer role at Northmarq?
The role is heavily focused on Salesforce development and integration. You will customize the platform, write Apex and Lightning Web Components, and build integrations that streamline commercial real estate transactions and financial operations.
Northmarq Software Engineer candidate reports ↗Where are the software engineering teams located?
Northmarq’s technology teams are primarily centered around the Twin Cities metro area in Minnesota, with offices in locations such as Bloomington, Minneapolis, and Saint Paul. The company typically operates on a hybrid model for these roles.
Northmarq Software Engineer candidate reports ↗How technical is the interview process?
The process is highly practical and conversational. Rather than administering abstract whiteboard algorithms, the interviewers focus on your actual project history, your understanding of Salesforce architecture, and your ability to design real-world systems.
Northmarq Software Engineer candidate reports ↗What is the typical timeline from the first call to an offer?
The interview process is streamlined, often consisting of just two rounds (a recruiter screen and a hiring manager interview). Candidates can generally expect to complete the process and receive feedback within two to three weeks.
Northmarq Software Engineer candidate reports ↗What certifications are highly valued for this position?
While hands-on project experience is the most critical factor, having certifications such as Salesforce Certified Platform Developer I or II is highly regarded and helps validate your technical expertise.
Northmarq Software Engineer candidate reports ↗What topics does Northmarq test in interviews?
Northmarq interviews most often cover Stakeholder Communication, Marketing Analytics, Data Integrity, Salesforce (CRM Platform), and Risk Analysis. The exact emphasis depends on the specific role you apply for.
Northmarq Software Engineer candidate reports ↗Sources & methodology 3 sources ↗
No official company page is cited. Rounds and questions come from candidate reports and PracHub editorial material; each source shows the date it was read.
- 01Northmarq Software Engineer candidate reports ↗
Company-reported rounds, questions and FAQ.
Candidate reports · Accessed 2026-09-22 - 02PracHub Software Engineer practice ↗
PracHub practice material, not company-reported.
PracHub page · Accessed 2026-09-22 - 03PracHub preparation framework ↗
PracHub preparation guidance.
PracHub page · Accessed 2026-09-22
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