As a Software Engineer at Origin Energy, you are at the intersection of critical energy infrastructure and modern digital transformation. You will contribute to the systems that power Australia, moving beyond standard application development to influence how energy is generated, managed, and distributed. This role is pivotal in driving the technical excellence required to support a transition toward more sustainable and efficient energy solutions. The work you perform involves navigating complex, large-scale systems where reliability and performance are non-negotiable. Whether you are working on network operations software, field commissioning tools, or core platform engineering, your contributions directly impact the operational efficiency of the business. Expect to solve problems that are both technically challenging and socially relevant, requiring a blend of precision engineering and forward-thinking architecture.
Initial Screening
reportedAn initial assessment to gauge your background and fit for the role.
What to demonstrate
- An initial assessment to gauge your background and fit for the role
- Depth in Software Development
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
reportedDeeper evaluations of your technical skills relevant to the position.
What to demonstrate
- Deeper evaluations of your technical skills relevant to the position
- Depth in Software Development
How to prepare
- Answer aloud and timed: What is your experience with CI/CD pipelines, and how do you ensure code quality before deployment?
- Answer aloud and timed: How do you balance the need for rapid feature delivery with the requirement for system stability?
Behavioral Interviews
reportedInterviews with key team members and leadership to assess cultural fit.
What to demonstrate
- Interviews with key team members and leadership to assess cultural fit
- Depth in Software Development
How to prepare
- Prepare three examples from your own work, each with a decision you made and an outcome you can quantify.
- Re-read the description of the behavioral interviews above and write down what you would ask to confirm before it.
PracHub editorial advice for the preparation topics above.
Structure your answers
Use the STAR method (Situation, Task, Action, Result) for behavioral questions to keep your responses concise and impactful.
Show your work
When solving technical problems, talk through your thought process out loud so the interviewer can follow your logic.
Ask questions
Prepare thoughtful questions about the team's current challenges or the company's technical roadmap; this shows genuine interest and engagement.
Choose a category, try a prompt, then open its approach, worked solution or follow-up when you need it.
Track a rolling failure rate per destination for circuit decisions
The egress service delivers about 1,500 webhooks per second across roughly 40,000 destinations, each call bounded by a 10 second timeout. Maintain, per destination, the failure rate over the trailing 60 seconds so a caller can ask before dispatch whether the circuit should open. Attempts arrive as (destination_id, finished_at_ms, outcome). Requirement: amortised O(1) per attempt, with total memory bounded by the destination count rather than by traffic. Give the structure, its exact memory, and the rule that stops a destination with three attempts from opening a circuit.
Approach
- Name the exact-deque version and then reject it as the default. Holding timestamps and advancing a tail pointer past anything older than now minus 60 seconds is a correct two-pointer window at amortised O(1) per attempt, but its memory tracks in-window traffic, so one destination in a retry storm holds hundreds of thousands of entries while thousands of quiet destinations hold none.
- Use a ring of 60 one-second buckets per destination, each bucket a pair of counters for attempts and failures. On an attempt, advance the ring by the elapsed whole seconds, zeroing at most min(elapsed, 60) buckets, then increment the head. That is amortised O(1) with a fixed footprint per destination.
- State the footprint: 60 buckets times two 4-byte counters is 480 bytes of payload per destination, so 40,000 destinations is roughly 20 to 25 MB with per-entry overhead, bounded by the catalogue rather than by the rate. The cost is granularity, since the oldest bucket ages out in whole seconds, which is far tighter than the decision needs.
- Require a minimum sample before the circuit may open. A destination with three attempts and three failures reads as 100 percent and is not evidence; a floor of roughly 20 attempts in the window makes the ratio meaningful, and below that floor use a run of consecutive failures as the trigger instead.
Follow-up
- The fleet is 30 instances and each sees roughly a thirtieth of a destination's traffic. Where does the rate actually live, and what does a per-instance answer get wrong?
- A destination answers in 9.5 seconds and succeeds. It is not failing but it is consuming your per-destination concurrency. What signal should open the circuit here?
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?
Find overlapping job attempts and peak concurrency from lease records
A day of job_run history yields about 50,000,000 attempt records: (job_run_id, job_type, attempt, started_at, finished_at which is NULL when the worker died, lease_expires_at). Leases expire on a clock, so a job that outran its lease ran twice. Produce (a) every job_run_id whose attempts overlapped in wall-clock time and (b) the peak number of simultaneously running attempts per job_type with the minute it occurred. Target O(n log n). State how you treat a NULL finished_at and what clock skew does to your answer.
Approach
- Define the interval before sorting anything: an attempt occupies [started_at, COALESCE(finished_at, lease_expires_at)). finished_at is observed and lease_expires_at is only a promise, so every attempt without a finish contributes an estimate and the whole result is a lower bound on overlap rather than an exact count.
- For peak concurrency, sweep: emit 2n endpoints, sort by (timestamp, kind) with ends ordered before starts at equal timestamps, then walk the sequence maintaining a counter per job_type and record each type's maximum with its timestamp. O(n log n) dominated by the sort, O(n) space, or O(1) extra if the sort is external and the walk streams.
- For overlap detection, do not compare attempts pairwise. A single global sort by (job_run_id, started_at) gives both the grouping and the order; within a group, keep the maximum end seen so far and report an overlap exactly when the next start is less than that running maximum, which is one linear pass after the sort.
- Half-open intervals matter and are easy to get wrong: with closed intervals an attempt ending at the same millisecond another begins reads as concurrency two, and across 50,000,000 records that artefact swamps the real signal.
Follow-up
- A handler is not idempotent and you have found 400 overlapping jobs. Which of them actually caused damage, and what would you query to find out?
- Peak concurrency for one job_type is 4 against a configured cap of 4. Is the cap working, or is the data hiding attempts that never started?
Find version gaps and relay lag with window functions
outbox_event holds event_id, aggregate_type, aggregate_id, aggregate_version, event_type, payload, status ('pending','published','dead'), attempts, created_at, published_at. A projection is missing rows and you must decide whether the relay skipped events or the consumer dropped them. Write three queries over the last seven days: one listing every aggregate_id whose published aggregate_version sequence has a hole, one giving per-day counts with a running total, and one returning the newest published event per aggregate. For each, say where the window function is evaluated relative to WHERE and LIMIT. PostgreSQL 16.
Approach
- Gaps: compute lead(aggregate_version) OVER (PARTITION BY aggregate_id ORDER BY aggregate_version) in a subquery, then filter next_version <> aggregate_version + 1 in the outer query. Window functions are evaluated after WHERE, GROUP BY and HAVING and before the outer ORDER BY and LIMIT, so the predicate cannot sit in the same WHERE clause and PostgreSQL 16 has no QUALIFY.
- Say what the seven-day filter does to the answer: it truncates every partition, so the first row per aggregate has no predecessor inside the window and a hole spanning the boundary is invisible. Widen the window, or join to resource.version as the authority for the true maximum.
- Running total: SELECT date_trunc('day', created_at) AS d, count() AS n, sum(count()) OVER (ORDER BY date_trunc('day', created_at) ROWS UNBOUNDED PRECEDING). An aggregate inside a window call is legal because grouping runs before windowing. The grouping key is unique per row here so ROWS and RANGE agree, but write the frame anyway — over ungrouped rows with tied timestamps the default RANGE frame pulls in every peer row and the total jumps.
- Newest per aggregate: DISTINCT ON (aggregate_id) ... ORDER BY aggregate_id, aggregate_version DESC is the cheap PostgreSQL-only form when an index matches that order; row_number() OVER (PARTITION BY aggregate_id ORDER BY aggregate_version DESC) = 1 is the portable form and needs a subquery for the same evaluation-order reason as the gap query.
Follow-up
- Relay failover redelivers events. Does a duplicate break the gap query, and how would you detect one from this table alone?
- Turn the gap check into a continuous monitor rather than a query someone runs after an incident. What does it watch?
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 ensure high availability and reliability in distributed systems?
How do you ensure high availability and reliability in distributed systems?
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 balance the need for rapid feature delivery with the requirement for system stability?
How do you balance the need for rapid feature delivery with the requirement for system stability?
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 your approach to debugging a production issue in a complex network environment?
Can you explain your approach to debugging a production issue in a complex network environment?
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 Origin Energy candidates report.
Prepare, practise & reflect
One practical outcome each day. Spend longer where you need it.
0 / 7 done01Map the Origin Energy loop
- Write out the reported sequence: Initial Screening, Technical Assessments, Behavioral 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 3 reported rounds, with the weakest marked.
02Work Software Development
- Spend the session on Software Development, which Origin Energy candidates report being tested on.
- Write one worked example in Software Development and time yourself on it.
Deliverable: One timed worked example in Software Development.
03Work Networking Operations
- Spend the session on Networking Operations, which Origin Energy candidates report being tested on.
- Write one worked example in Networking Operations and time yourself on it.
Deliverable: One timed worked example in Networking Operations.
04Work Network Reliability & Availability
- Spend the session on Network Reliability & Availability, which Origin Energy candidates report being tested on.
- Write one worked example in Network Reliability & Availability and time yourself on it.
Deliverable: One timed worked example in Network Reliability & Availability.
05Answer out loud: Technical Proficiency and Domain Knowledge
- Answer aloud, timed: How do you ensure high availability and reliability in distributed systems?
- Answer aloud, timed: Can you explain your approach to debugging a production issue in a complex network environment?
Deliverable: Spoken answers to 2 reported Technical Proficiency and Domain Knowledge question(s), under time.
06Answer out loud: Behavioral and Situational Leadership
- Answer aloud, timed: Describe a time you had to explain a complex technical problem to a non-technical stakeholder.
- Answer aloud, timed: Tell me about a time you identified a flaw in a system; what steps did you take to address it?
Deliverable: Spoken answers to 2 reported Behavioral and Situational Leadership question(s), under time.
07Dry run for Origin Energy
- Run one full mock under time, then write down the two questions you most want to ask your interviewers.
Deliverable: A completed timed mock and two questions to ask.
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.
What is your experience with CI/CD pipelines, and how do you ensure code quality before deployment?
What is your experience with CI/CD pipelines, and how do you ensure code quality before deployment?
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 with cloud-based infrastructure and managing scalability.
Describe your experience with cloud-based infrastructure and managing scalability.
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 explain a complex technical problem to a non-technical stakeholder.
Describe a time you had to explain a complex technical problem to a non-technical stakeholder.
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 identified a flaw in a system; what steps did you take to address it?
Tell me about a time you identified a flaw in a system; what steps did you take to address 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 handle disagreements with team members regarding architectural decisions?
How do you handle disagreements with team members regarding architectural decisions?
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?
Give an example of how you have mentored a junior engineer or improved team processes.
Give an example of how you have mentored a junior engineer or improved team processes.
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 your work when faced with competing deadlines and shifting business needs?
How do you prioritize your work when faced with competing deadlines and shifting business needs?
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
What is your experience with CI/CD pipelines, and how do you ensure code quality before deployment?
- 02
Describe your experience with cloud-based infrastructure and managing scalability.
- 03
Describe a time you had to explain a complex technical problem to a non-technical stakeholder.
- 04
Tell me about a time you identified a flaw in a system; what steps did you take to address it?
How much time should I dedicate to preparing for the interview?
Dedicate at least 1–2 weeks of focused preparation. Use this time to revisit your past projects and practice articulating your technical decisions clearly.
Origin Energy Software Engineer candidate reports ↗What is the most important trait for a successful candidate?
Beyond technical skills, the ability to communicate complex ideas clearly and a willingness to work collaboratively with non-technical teams are highly valued at Origin Energy.
Origin Energy Software Engineer candidate reports ↗Will I be tested on specific technologies?
The interview will focus on your ability to solve problems, but you should be prepared to discuss the technologies you have used in your previous roles in depth.
Origin Energy Software Engineer candidate reports ↗What is the culture like at Origin Energy?
The culture is collaborative, focused on safety, and driven by the goal of transforming energy systems. You will work with teams that value reliability and innovation.
Origin Energy Software Engineer candidate reports ↗How many interview rounds does Origin Energy have for a Software Engineer role, and what are the stages?
Origin Energy’s Software Engineer interview process runs in three stages: Initial Screening, Technical Assessments, and Behavioral Interviews. The sequence starts with an initial assessment of background and fit, then moves to deeper technical evaluations, and ends with interviews focused on cultural fit with key team members and leadership. Exact round counts beyond these named stages are not specified in the available information.
Origin Energy Software Engineer candidate reports ↗How hard are Origin Energy Software Engineer interviews compared to other companies?
Candidate-reported difficulty is listed as average for Origin Energy Software Engineer interviews. In the same dataset, there is no completed offer-rate percentage reported for this role, so you cannot rely on it for expectations. If you want to gauge difficulty, focus on preparing for both technical and behavioral components rather than only coding.
Origin Energy Software Engineer candidate reports ↗What topics does Origin Energy test for Software Engineer interviews?
Preparation should prioritize Software Development and operational reliability topics like Network Reliability and Availability, Troubleshooting and Root Cause Analysis, Monitoring and Alerting, and Incident Response. The role also connects to operational tooling areas such as Field Commissioning and Configuration Management, along with networking operations themes. In addition, expect interview coverage around system design and architecture trade-offs, and coding that emphasizes maintainable, best-practice implementation rather than only algorithmic puzzles.
Origin Energy Software Engineer candidate reports ↗What should I prepare for if I get a debugging or reliability question at Origin Energy for Software Engineer?
Be ready to explain how you debug production issues in a complex network environment and how you ensure high availability and reliability in distributed systems. The preparation emphasis also includes monitoring and observability strategies, since interviewers evaluate how you keep systems healthy in operational settings. Pair your approach with practical thinking about edge cases, incident response, and root cause analysis.
Origin Energy Software Engineer candidate reports ↗What does Origin Energy ask about in behavioral interviews for a Software Engineer?
Behavioral interviews cover how you collaborate and communicate, including explaining complex technical problems to non-technical stakeholders. You should also have examples of identifying system flaws and the steps you took to address them, plus how you handle architectural disagreements cross-functionally. Mentoring and prioritization under shifting deadlines are also aligned with the behavioral patterns described.
Origin Energy 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.
- 01Origin Energy 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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