Sikich hires Software Engineers; this guide collects what candidates report about the process.
Initial Screening
reportedConversation with HR or a hiring manager focusing on your background, technical alignments, and career goals.
What to demonstrate
- Conversation with HR or a hiring manager focusing on your background, technical alignments, and career goals
- Depth in Ticket management
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.
Deep-Dive Technical Round
reportedExploration of your past experience with server-side technologies, cloud environments, O365, and networking.
What to demonstrate
- Exploration of your past experience with server-side technologies, cloud environments, O365, and networking
- Depth in Ticket management
How to prepare
- Answer aloud and timed: How do you diagnose and resolve a severe latency issue in a hybrid cloud networking environment?
- Answer aloud and timed: What is your process for deploying a server-side update without causing downtime for active business users?
Client-Focused Situational Round
reportedEvaluation of how you handle high-pressure scenarios, prioritize tasks, and manage ticket flows.
What to demonstrate
- Evaluation of how you handle high-pressure scenarios, prioritize tasks, and manage ticket flows
- Depth in Ticket management
How to prepare
- Answer aloud and timed: How do you handle a high-pressure situation when multiple client systems experience issues simultaneously?
- Answer aloud and timed: Walk us through your process for prioritizing tasks when your ticket queue is backed up and multiple stakeholders claim their issue is the highest priority.
PracHub editorial advice for the preparation topics above.
Clarify compensation early
Historical candidate data indicates that salary ranges can vary significantly based on specialization, level, and geography. Discuss your expectations during your initial HR phone screen to ensure alignment.
Use the STAR method
When answering situational questions in the client round, structure your responses using the Situation, Task, Action, and Result framework. Focus heavily on the "Action" you took to resolve the client's issue and the business "Result."
Brush up on infrastructure basics
Even if you are interviewing for a software-focused role, having a solid grasp of O365 troubleshooting, server-side hosting, and basic networking concepts is highly valued at Sikich.
Choose a category, try a prompt, then open its approach, worked solution or follow-up when you need it.
Merge partitioned event streams into one ordered feed with bounded lateness
The read-model service consumes 64 log partitions carrying about 4,000 events per second in total. Each partition is ordered within itself, but partitions drift by up to 30 seconds, and the activity feed must present a tenant's events in occurred_at order. Produce the merge. State its complexity, the buffer it requires in events and in bytes, what happens when one partition is idle, and what you do with an event that arrives after you have already emitted its position. Payloads average 1 KB.
Approach
- Merge with a min-heap over the 64 partition heads keyed on (occurred_at, event_id): O(log P) per event and O(n log P) overall. The tie-break on event_id is what makes the output deterministic when two partitions carry the same millisecond, which matters because the feed is paginated and a non-deterministic order reorders pages under the reader.
- Emitting the heap head is only correct once every partition has produced everything up to that timestamp, so the emit condition is a watermark: the minimum across partitions of the highest occurred_at seen, less the allowed lateness. Events are held until the watermark passes them, which is what turns individually ordered streams into a jointly ordered one.
- Size the buffer from the lateness rather than guessing: 4,000 events per second times 30 seconds is 120,000 buffered events, and at 1 KB each about 120 MB of heap. That number is the real price of the ordering guarantee and belongs in front of whoever asked for it.
- Handle the idle partition explicitly, because it fails the feed rather than corrupting it: a partition with no traffic never advances its own maximum, so the watermark freezes and output stops entirely. Either every partition emits a periodic idle marker carrying the broker's current time, or the watermark falls back to wall clock for a partition silent beyond a threshold.
Follow-up
- The lateness budget is raised to five minutes. What is the new buffer, and what besides memory changes?
- The consumer restarts. Where does it resume from, and what does the feed look like for the first 30 seconds?
Diff a projection against the primary without per-row point reads
The listing projection has drifted and some rows show a stale version. The primary holds 40,000,000 resource rows across 12,000 tenants while serving 1,200 writes and 14,000 reads per second. The obvious repair, reading each resource row and comparing its version against the projection, is correct and would eventually finish. Explain precisely why it is unacceptable here, then give a diff that finds the differing rows, state its complexity, and make it safe to run against a live primary. Replication lag is usually under 100 ms and is not bounded.
Approach
- Quantify the naive cost rather than calling it slow: 40,000,000 point reads at even 0.5 ms each is over five hours serialised, and the only lever is concurrency, which is exactly what you cannot spend. The primary's pool is sized for the write path, and 40,000,000 random reads evict the buffer cache that sustains the 85 percent cache hit rate, so the audit degrades the system it is auditing.
- Replace random access with one ordered pass per side. Both sides can be read in (tenant_id, resource_id) order, which is a sequential scan on each and a merge join in O(n) time and O(1) memory. For a dense diff that is the whole answer, and it reads the primary once instead of 40,000,000 times.
- For the expected sparse case, compare range hashes instead of rows: partition the key space, compute per range an order-independent aggregate over hash(resource_id, version), compare aggregates, and descend only into ranges that differ. With d differing rows and branching factor B, at most d ranges mismatch per level, so the drill-down examines O(d log_B(n/d)) ranges and reads full rows only in mismatching leaves.
- Aggregate with a sum modulo 2^64 or a multiset hash, never XOR. XOR is order-independent but self-cancelling, so two rows wrong in the same way, or a row duplicated on one side, leave the range aggregate matching and the range is declared clean.
Follow-up
- The diff reports 900 stale rows. How do you decide between patching those rows and rebuilding the projection from resource_revision?
- Same job, but the projection lives in a search index that cannot be scanned in key order. What changes?
Collapse a redelivered event batch into per-aggregate high-water marks
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
- 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.
- 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.
- 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.
- 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?
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?
Denormalise tenant onto revisions and backfill it live
resource_revision (revision_id, resource_id, version, actor_user_id, change_kind, patch, request_id, created_at) has 400M rows and no tenant column; tenant_id lives only on resource. Two reads need it: a tenant-scoped audit feed ordered by created_at DESC, and an offboarding purge. Both join back to resource today. Justify adding tenant_id to resource_revision against those two reads, name the anomaly the copy introduces and the constraint that prevents it, then give the ordered migration for a live table taking 1.2k writes/second — the lock each step takes, how the backfill is batched, and where each step stops being reversible. PostgreSQL 16.
Approach
- Justify from the access path rather than from taste. Without the column, the audit feed either scans resource_revision by created_at and discards other tenants' rows, or resolves the tenant's resource_ids first and probes with them — both proportional to the tenant's whole history rather than to one page. With (tenant_id, created_at DESC, revision_id DESC) it is a seek that stops at 50 rows, and the purge becomes a ranged delete instead of a join.
- Name the cost exactly: a second copy of a fact can disagree with the first. Make the disagreement unwritable rather than documented — add UNIQUE (resource_id, tenant_id) on resource so it can serve as a foreign-key target, then FOREIGN KEY (resource_id, tenant_id) REFERENCES resource (resource_id, tenant_id) on the revision table. A revision can then only ever carry its parent's tenant.
- Step one, expand: ALTER TABLE resource_revision ADD COLUMN tenant_id BIGINT NULL, with no default, so it is a catalogue change and no rewrite. It still needs ACCESS EXCLUSIVE for an instant, and that instant queues behind the longest open transaction on the table while every later query queues behind it — set lock_timeout to 2s and retry rather than wait.
- Step two, dual-write: deploy the writer that populates tenant_id on every new revision while reads still use the join. Reversible by redeploying the previous build, because nothing reads the column yet.
Follow-up
- The backfill is half finished and a rollback is required. What state is the table in, and what does the previous build do with a half-populated column?
- How do you verify the backfill actually finished, given rows are still being inserted while it runs?
How do you diagnose and resolve a severe latency issue in a hybrid cloud networking environment?
How do you diagnose and resolve a severe latency issue in a hybrid cloud networking environment?
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?
What is your process for deploying a server-side update without causing downtime for active business users?
What is your process for deploying a server-side update without causing 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?
Walk us through your process for prioritizing tasks when your ticket queue is backed up and multiple stakehold
Walk us through your process for prioritizing tasks when your ticket queue is backed up and multiple stakeholders claim their issue is the highest priority.
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?
How do you manage client expectations when a technical solution is going to take longer than originally promis
How do you manage client expectations when a technical solution is going to take longer than originally promised?
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 architectural patterns do you rely on when designing custom integrations within a Salesforce environment?
What architectural patterns do you rely on when designing custom integrations within a Salesforce environment?
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 ensure robust security protocols are maintained when connecting external databases to a Salesforce
How do you ensure robust security protocols are maintained when connecting external databases to a Salesforce instance?
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?
Explain your approach to designing a secure, scalable network architecture for a multi-location enterprise cli
Explain your approach to designing a secure, scalable network architecture for a multi-location enterprise client.
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 troubleshooting a complex Microsoft 365 integration issue that is affecting user authentic
How do you approach troubleshooting a complex Microsoft 365 integration issue that is affecting user authentication?
Approach
- Establish what changed and when, before forming any theory.
- Pick a bisection that eliminates candidates whichever way it turns out.
- Check the instrumentation before believing the symptom.
- 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?
Built from the rounds and topics Sikich candidates report.
Prepare, practise & reflect
One practical outcome each day. Spend longer where you need it.
0 / 7 done01Map the Sikich loop
- Write out the reported sequence: Initial Screening, Deep-Dive Technical Round, Client-Focused Situational Round.
- 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.
02Work Ticket management
- Spend the session on Ticket management, which Sikich candidates report being tested on.
- Write one worked example in Ticket management and time yourself on it.
Deliverable: One timed worked example in Ticket management.
03Work Task prioritization
- Spend the session on Task prioritization, which Sikich candidates report being tested on.
- Write one worked example in Task prioritization and time yourself on it.
Deliverable: One timed worked example in Task prioritization.
04Work Salesforce development (Salesforce Senior Developer)
- Spend the session on Salesforce development (Salesforce Senior Developer), which Sikich candidates report being tested on.
- Write one worked example in Salesforce development (Salesforce Senior Developer) and time yourself on it.
Deliverable: One timed worked example in Salesforce development (Salesforce Senior Developer).
05Answer out loud: Cloud, Server-Side & Infrastructure
- Answer aloud, timed: How do you approach troubleshooting a complex Microsoft 365 integration issue that is affecting user authentication?
- Answer aloud, timed: Walk me through your experience managing server-side technologies and cloud infrastructure in your previous roles.
Deliverable: Spoken answers to 2 reported Cloud, Server-Side & Infrastructure question(s), under time.
06Answer out loud: Client Management & Prioritization
- Answer aloud, timed: How do you handle a high-pressure situation when multiple client systems experience issues simultaneously?
- Answer aloud, timed: Walk us through your process for prioritizing tasks when your ticket queue is backed up and multiple stakeholders claim their issue is the highest priority.
Deliverable: Spoken answers to 2 reported Client Management & Prioritization question(s), under time.
07Answer out loud: Platform-Specific & Network Engineering
- Answer aloud, timed: What architectural patterns do you rely on when designing custom integrations within a Salesforce environment?
- Answer aloud, timed: How do you ensure robust security protocols are maintained when connecting external databases to a Salesforce instance?
Deliverable: Spoken answers to 2 reported Platform-Specific & Network Engineering 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.
Walk me through your experience managing server-side technologies and cloud infrastructure in your previous ro
Walk me through your experience managing server-side technologies and cloud infrastructure in your previous roles.
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 a high-pressure situation when multiple client systems experience issues simultaneously?
How do you handle a high-pressure situation when multiple client systems experience issues simultaneously?
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 explain a highly complex server-side or networking issue to a non-technical cl
Describe a time when you had to explain a highly complex server-side or networking issue to a non-technical client.
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
Walk me through your experience managing server-side technologies and cloud infrastructure in your previous roles.
- 02
How do you handle a high-pressure situation when multiple client systems experience issues simultaneously?
- 03
Describe a time when you had to explain a highly complex server-side or networking issue to a non-technical client.
How technical is the first round of interviews?
The first round after the HR screen is highly technical and deeply practical. Rather than focusing on abstract algorithmic puzzles, interviewers will ask you to explain your real-world experience with server-side technologies, cloud management, O365, and networking.
Sikich Software Engineer candidate reports ↗What is the "Client Round" looking for?
The client round evaluates your situational judgment, prioritization logic, and communication skills under pressure. Interviewers want to see how you manage a heavy ticket flow and how you communicate technical issues to clients.
Sikich Software Engineer candidate reports ↗Does Sikich support remote work for Software Engineers?
Yes, Sikich offers remote and hybrid working arrangements depending on the specific role, client requirements, and location. Be sure to clarify the expectations for your specific position during the initial HR screen.
Sikich Software Engineer candidate reports ↗What differentiates a successful candidate at Sikich?
The most successful candidates are those who possess both strong technical skills and a consultative mindset. Showing that you care about the business impact of your technical decisions is key to standing out.
Sikich Software Engineer candidate reports ↗What topics does Sikich test in interviews?
Sikich interviews most often cover Stakeholder Management, SQL, Professionalism, Python, and Problem Solving. The exact emphasis depends on the specific role you apply for.
Sikich 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.
- 01Sikich 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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