As a Software Engineer at Domain Group, you are at the heart of one of Australia’s most influential digital marketplaces. You will be responsible for building, scaling, and optimizing the platforms that millions of users rely on to make significant life decisions, such as buying, selling, or renting property. Whether working on core web infrastructure or specialized product features, your code directly impacts the user experience and the efficiency of the real estate ecosystem. This role demands a blend of technical precision and product-minded thinking. You aren't just writing code; you are solving complex challenges related to high-traffic systems, data-driven personalization, and high-performance web architecture. You will collaborate closely with cross-functional teams, including product managers and designers, to turn abstract requirements into robust, maintainable, and scalable solutions that keep Domain Group at the forefront of the industry. ##### Tip The roles at Domain Group are highly collaborative. Expect to demonstrate not just your technical proficiency, but your ability to communicate complex ideas to non-technical stakeholders.
Recruiter Screen
reportedInitial screening call with a recruiter to assess your background and fit for the role.
What to demonstrate
- Initial screening call with a recruiter to assess your background and fit for the role
- Depth in Team Lead / Technical Leadership
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 Assessments
reportedA series of technical evaluations that may include live coding, system design discussions, and behavioral interviews.
What to demonstrate
- A series of technical evaluations that may include live coding, system design discussions, and behavioral interviews
- Depth in Team Lead / Technical Leadership
How to prepare
- Answer aloud and timed: How do you ensure high availability and performance in a microservices architecture?
- Answer aloud and timed: Explain your approach to optimizing page load times for a content-heavy web application.
Team Interaction
reportedOpportunities to interact with different team members to understand team dynamics and culture.
What to demonstrate
- Opportunities to interact with different team members to understand team dynamics and culture
- Depth in Team Lead / Technical Leadership
How to prepare
- Answer aloud and timed: How do you handle data consistency in a distributed system?
- Answer aloud and timed: Describe a time you had to refactor legacy code to improve performance.
Final Round Interviews
reportedConcluding interviews focusing on strategic, architectural, and behavioral discussions.
What to demonstrate
- Concluding interviews focusing on strategic, architectural, and behavioral discussions
- Depth in Team Lead / Technical Leadership
How to prepare
- Answer aloud and timed: How do you approach debugging a production issue that is difficult to reproduce?
- Answer aloud and timed: Write a function to handle [specific data structure] manipulation efficiently.
PracHub editorial advice for the preparation topics above.
Use the STAR method
When answering behavioral questions, structure your responses using the Situation, Task, Action, and Result framework to ensure clarity and impact.
Speak your thoughts aloud
During coding and system design rounds, narrate your thought process. Interviewers want to see how you approach problems, not just your final solution.
Prepare your own questions
Always have 3–4 thoughtful questions prepared for your interviewers, such as "How does the team balance new feature development with technical debt?"
Research the product
Spend time using the Domain Group website and app. Understanding the user journey will make your technical suggestions feel much more grounded and relevant.
Choose a category, try a prompt, then open its approach, worked solution or follow-up when you need it.
Write a function to handle [specific data structure] manipulation efficiently.
Write a function to handle [specific data structure] manipulation efficiently.
Approach
- Restate the input: its shape, its size, and what is guaranteed about it.
- Name the brute-force solution and its complexity before improving on it.
- Choose the data structure from the access pattern, not from familiarity.
- 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 ensure your code is maintainable for other team members?
How do you ensure your code is maintainable for other team members?
Approach
- Restate the input: its shape, its size, and what is guaranteed about it.
- Name the brute-force solution and its complexity before improving on it.
- Choose the data structure from the access pattern, not from familiarity.
- 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?
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?
Replace offset paging on the resource feed with keyset
resource holds resource_id, tenant_id, owner_user_id, title, body_ref, version, status ('draft','active','archived','deleted'), created_at, updated_at, deleted_at, with an index on (tenant_id, status, updated_at DESC, resource_id DESC). The listing endpoint returns active resources for one tenant, newest update first, 50 per page, today with LIMIT 50 OFFSET n. Tenants reach page 400 and rows are created while they read. Write the keyset query, define what the cursor carries and how it is encoded, and say which part of the index each predicate uses. Assume PostgreSQL 16.
Approach
- Name the two failures separately. OFFSET 20000 makes the server produce and discard 20,000 rows, so page cost grows with depth rather than with page size. Independently, any write that changes how many rows sort above the offset moves the window between two fetches, and the direction decides which anomaly you get: an insert lands at the head of updated_at DESC and pushes already-returned rows down past the boundary, so they are returned a second time; a delete above the offset, or a row whose updated_at is bumped above the cursor, pulls rows up and one is never returned at all. Nothing in the response reveals either.
- Write the seek: WHERE tenant_id = $1 AND status = 'active' AND (updated_at, resource_id) < ($2, $3) ORDER BY updated_at DESC, resource_id DESC LIMIT 50. The row-value comparison is one index range rather than a disjunction, and both columns are NOT NULL, which is what makes that comparison well defined.
- Map each predicate onto the index: tenant_id and status are equality on the leading columns, (updated_at, resource_id) is the range, and the ORDER BY matches the index order so no Sort node appears and the scan stops after 50 rows. The DESC in the definition only matters for mixed directions — a plain ascending btree on the same columns is read backwards for this query.
- Put both sort columns in the cursor and nothing the client can tamper with into another tenant: base64 of (updated_at, resource_id), validated server-side, with tenant_id taken from the principal.
Follow-up
- The client asks for 'jump to page 400'. What do you offer instead, and what does the honest version cost?
- Sort order becomes user-selectable across four columns. How many indexes is that, and which would you refuse to add?
Explain why the owner filter ignores the listing index
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
- 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.
- 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.
- 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.
- 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?
How would you design a high-traffic property listing search service?
How would you design a high-traffic property listing search service?
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 are the trade-offs between different database technologies for a real-time notification system?
What are the trade-offs between different database technologies for a real-time notification system?
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 ensure high availability and performance in a microservices architecture?
How do you ensure high availability and performance in a microservices architecture?
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?
Explain your approach to optimizing page load times for a content-heavy web application.
Explain your approach to optimizing page load times for a content-heavy web application.
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 is your strategy for writing unit and integration tests for complex logic?
What is your strategy for writing unit and integration tests for complex logic?
Approach
- Say who the caller is and what they do when the call fails halfway.
- Define the identity of a request so a retry cannot double-apply it.
- Separate accepted, pending, failed and confirmed; they are different facts.
- Design the error taxonomy before the success shape; callers branch on it.
Follow-up
- What happens if the caller retries after a timeout?
- How does a client discover it is on an old version of this contract?
How do you approach debugging a production issue that is difficult to reproduce?
How do you approach debugging a production issue that is difficult to reproduce?
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 Domain Group candidates report.
Prepare, practise & reflect
One practical outcome each day. Spend longer where you need it.
0 / 7 done01Map the Domain Group loop
- Write out the reported sequence: Recruiter Screen, Technical Assessments, Team Interaction, Final Round Interviews.
- For each round, write one sentence on what it is judging, from the description above, and mark the one you are least ready for.
Deliverable: A one-page map of the 4 reported rounds, with the weakest marked.
02Work Team Lead / Technical Leadership
- Spend the session on Team Lead / Technical Leadership, which Domain Group candidates report being tested on.
- Write one worked example in Team Lead / Technical Leadership and time yourself on it.
Deliverable: One timed worked example in Team Lead / Technical Leadership.
03Work Core Web / Web Engineering
- Spend the session on Core Web / Web Engineering, which Domain Group candidates report being tested on.
- Write one worked example in Core Web / Web Engineering and time yourself on it.
Deliverable: One timed worked example in Core Web / Web Engineering.
04Work Software Engineering Fundamentals
- Spend the session on Software Engineering Fundamentals, which Domain Group candidates report being tested on.
- Write one worked example in Software Engineering Fundamentals and time yourself on it.
Deliverable: One timed worked example in Software Engineering Fundamentals.
05Answer out loud: Technical & Architectural Design
- Answer aloud, timed: How would you design a high-traffic property listing search service?
- Answer aloud, timed: What are the trade-offs between different database technologies for a real-time notification system?
Deliverable: Spoken answers to 2 reported Technical & Architectural Design question(s), under time.
06Answer out loud: Coding & Problem Solving
- Answer aloud, timed: Describe a time you had to refactor legacy code to improve performance.
- Answer aloud, timed: How do you approach debugging a production issue that is difficult to reproduce?
Deliverable: Spoken answers to 2 reported Coding & Problem Solving question(s), under time.
07Answer out loud: Behavioral & Leadership
- Answer aloud, timed: Tell me about a time you had a technical disagreement with a peer. How did you resolve it?
- Answer aloud, timed: How do you prioritize tasks when you have multiple competing deadlines?
Deliverable: Spoken answers to 2 reported Behavioral & Leadership 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.
How do you handle data consistency in a distributed system?
How do you handle data consistency in a distributed system?
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 you had to refactor legacy code to improve performance.
Describe a time you had to refactor legacy code to improve performance.
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 had a technical disagreement with a peer. How did you resolve it?
Tell me about a time you had a technical disagreement with a peer. How did you resolve it?
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 prioritize tasks when you have multiple competing deadlines?
How do you prioritize tasks when you have multiple competing deadlines?
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 your experience mentoring junior engineers or conducting code reviews.
Describe your experience mentoring junior engineers or conducting code reviews.
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 ambiguity in project requirements?
How do you handle ambiguity in project requirements?
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?
What motivates you to stay updated with the latest software engineering trends?
What motivates you to stay updated with the latest software engineering trends?
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
How do you handle data consistency in a distributed system?
- 02
Describe a time you had to refactor legacy code to improve performance.
- 03
Tell me about a time you had a technical disagreement with a peer. How did you resolve it?
- 04
How do you prioritize tasks when you have multiple competing deadlines?
How long does the interview process typically take?
The process usually spans 3–5 weeks from the initial recruiter screen to a final decision, though this can vary based on scheduling and team needs.
Domain Group Software Engineer candidate reports ↗How much preparation time should I dedicate to coding vs. system design?
For Senior roles, invest roughly 60% of your time in system design and 40% in coding/algorithms, as architectural decision-making becomes a primary differentiator.
Domain Group Software Engineer candidate reports ↗What is the team culture like at Domain Group?
The culture is highly collaborative, fast-paced, and centered on user-centric innovation. Engineers are encouraged to take ownership and propose solutions to improve the product.
Domain Group Software Engineer candidate reports ↗What topics does Domain Group test in interviews?
Domain Group interviews most often cover Statistical Analysis, Problem Solving, Stakeholder Communication, Support Vector Machines (SVM), and Marketing Analytics. The exact emphasis depends on the specific role you apply for.
Domain Group 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.
- 01Domain Group 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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