At Speedway, a Software Engineer plays a crucial role in driving the digital and operational technologies that power one of the nation's leading convenience store chains. Far from a standard retail support role, software engineering at Speedway involves building, maintaining, and scaling the critical systems that keep thousands of retail locations running smoothly. From point-of-sale (POS) systems and back-office logistics to inventory management and customer-facing loyalty platforms, your code directly impacts millions of transactions and customers daily. The engineering team is tasked with solving unique retail and transactional challenges at scale. This includes optimizing database queries for high-volume transactions, integrating legacy systems with modern cloud infrastructure, and ensuring high availability across distributed networks. As a Software Engineer, you will collaborate with cross-functional teams to deliver reliable, secure, and user-friendly software solutions that streamline store operations and elevate the guest experience. This role requires a balance of technical capability, adaptability, and business awareness. Whether you are working on backend services, desktop applications for store hardware, or mobile integrations, your contributions will directly support 's mission of providing fast, efficient, and friendly service.
Online Application
reportedSubmit your application online to begin the interview process.
What to demonstrate
- Submit your application online to begin the interview process
- Depth in Software Engineering Fundamentals
How to prepare
- Answer aloud and timed: Why do you want to be a Software Engineer at Speedway?
- Answer aloud and timed: What do you expect to learn or achieve during your time in this role or co-op?
Asynchronous Digital Interview
reportedRecord video and audio responses to behavioral and motivational questions using platforms like HireVue.
What to demonstrate
- Record video and audio responses to behavioral and motivational questions using platforms like HireVue
- Depth in Software Engineering Fundamentals
How to prepare
- Answer aloud and timed: Can you describe a time when you had to work with someone who had a different working style than yours?
- Answer aloud and timed: How do you handle tight deadlines or shifting project priorities?
Formal Interview
reportedParticipate in a conversational interview, either virtually or in-person, with a recruiter or engineering manager.
What to demonstrate
- Participate in a conversational interview, either virtually or in-person
- With a recruiter or engineering manager
How to prepare
- Answer aloud and timed: What motivated you to pursue a career in software engineering?
- Answer aloud and timed: Walk me through a recent technical project you worked on and the specific technologies you chose.
PracHub editorial advice for the preparation topics above.
Proactively share your technical depth
During behavioral and conversational rounds, do not wait for the interviewer to ask deep technical questions. Take the initiative to explain the technical architecture, database schemas, and coding decisions behind your projects.
Practice your video delivery
Since the initial screen is recorded, practice speaking clearly into a camera. Ensure your background is tidy, your lighting is good, and you keep your answers within the allotted time limits.
Understand the retail context
Research how technology drives modern convenience store operations. Having a basic understanding of supply chain logistics, loyalty programs, and POS systems will help you stand out.
Prepare thoughtful questions
At the end of the live interview, ask insightful questions about the team's current technical challenges, their development stack, and how they measure success for a Software Engineer.
Choose a category, try a prompt, then open its approach, worked solution or follow-up when you need it.
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?
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?
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?
Write the update path that detects a concurrent edit
resource carries version INT NOT NULL DEFAULT 1. resource_revision holds revision_id, resource_id, version, actor_user_id, change_kind, patch JSONB, request_id, created_at with UNIQUE (resource_id, version). outbox_event holds aggregate_type, aggregate_id, aggregate_version, event_type, payload, status. A PUT carries the version the client read. Write the exact statements for the single transaction that applies the edit, records the revision and enqueues 'resource.updated', and give the handler's branch on zero affected rows. Then say what PostgreSQL 16 does under READ COMMITTED when two of these updates hit one row at once.
Approach
- One transaction, three writes, no network call inside it: UPDATE resource SET title = $3, version = version + 1, updated_at = now() WHERE resource_id = $1 AND tenant_id = $4 AND version = $2; then INSERT the resource_revision row at version $2 + 1; then INSERT the outbox_event row at the same aggregate_version. The event goes to a table rather than a broker because no transaction spans both.
- Branch on the affected-row count before doing anything else. Zero has three causes — stale version, wrong tenant, row gone — so re-read once and map to 409 carrying the current version, or 404 for an id outside the caller's tenant, which also stops the endpoint confirming that another tenant's id exists.
- State the engine behaviour instead of assuming it. Under READ COMMITTED the second UPDATE blocks on the row lock, and when the first commits PostgreSQL re-evaluates the WHERE clause against the newly committed row, so the version predicate now fails and the statement reports zero rows. Under REPEATABLE READ the identical collision raises SQLSTATE 40001 instead, so the handler must fold both shapes into one conflict response.
- Keep UNIQUE (resource_id, version) even though the predicate already serialises writers. It is what makes a lost update unwritable if any other path ever reaches the revision table, and it converts a logic bug into 23505 rather than into a silently missing history row.
Follow-up
- A client sends the version it read ten minutes ago and the resource has moved three versions. What is in your 409 so it can resolve the conflict without a full re-fetch?
- Two editors, two disjoint fields, no overlap. Does your answer still refuse the second write, and should it?
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?
Walk me through a recent technical project you worked on and the specific technologies you chose.
Walk me through a recent technical project you worked on and the specific technologies you chose.
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 a technical concept you recently learned to someone with a non-technical background.
Explain a technical concept you recently learned to someone with a non-technical background.
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 your code is reliable and performant before deploying it?
How do you ensure your code is reliable and performant before deploying it?
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 approach debugging a complex issue in a system you did not write?
How do you approach debugging a complex issue in a system you did not write?
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 Speedway candidates report.
Prepare, practise & reflect
One practical outcome each day. Spend longer where you need it.
0 / 7 done01Map the Speedway loop
- Write out the reported sequence: Online Application, Asynchronous Digital Interview, Formal 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 3 reported rounds, with the weakest marked.
02Work Software Engineering Fundamentals
- Spend the session on Software Engineering Fundamentals, which Speedway 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.
03Work Technical Knowledge Communication
- Spend the session on Technical Knowledge Communication, which Speedway candidates report being tested on.
- Write one worked example in Technical Knowledge Communication and time yourself on it.
Deliverable: One timed worked example in Technical Knowledge Communication.
04Work Interview Questioning & Articulation
- Spend the session on Interview Questioning & Articulation, which Speedway candidates report being tested on.
- Write one worked example in Interview Questioning & Articulation and time yourself on it.
Deliverable: One timed worked example in Interview Questioning & Articulation.
05Answer out loud: Behavioral and Motivational
- Answer aloud, timed: Why do you want to be a Software Engineer at Speedway?
- Answer aloud, timed: What do you expect to learn or achieve during your time in this role or co-op?
Deliverable: Spoken answers to 2 reported Behavioral and Motivational question(s), under time.
06Answer out loud: Technical and Problem-Solving
- Answer aloud, timed: Walk me through a recent technical project you worked on and the specific technologies you chose.
- Answer aloud, timed: How do you approach debugging a complex issue in a system you did not write?
Deliverable: Spoken answers to 2 reported Technical and Problem-Solving question(s), under time.
07Dry run for Speedway
- 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.
Why do you want to be a Software Engineer at Speedway?
Why do you want to be a Software Engineer at Speedway?
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 do you expect to learn or achieve during your time in this role or co-op?
What do you expect to learn or achieve during your time in this role or co-op?
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?
Can you describe a time when you had to work with someone who had a different working style than yours?
Can you describe a time when you had to work with someone who had a different working style than yours?
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 tight deadlines or shifting project priorities?
How do you handle tight deadlines or shifting project priorities?
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 motivated you to pursue a career in software engineering?
What motivated you to pursue a career in software engineering?
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 optimize a database query or improve system performance.
Describe a time you had to optimize a database query or improve system 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?
- 01
Why do you want to be a Software Engineer at Speedway?
- 02
What do you expect to learn or achieve during your time in this role or co-op?
- 03
Can you describe a time when you had to work with someone who had a different working style than yours?
- 04
How do you handle tight deadlines or shifting project priorities?
How technical is the Speedway Software Engineer interview?
The interview process focuses heavily on practical application, behavioral alignment, and team fit. While you may not face complex whiteboard algorithm puzzles, you must be prepared to speak deeply about your past technical work, database design, and coding practices.
Speedway Software Engineer candidate reports ↗What is the typical timeline for the hiring process?
The process is known for being relatively fast and efficient. Candidates often complete the entire process, from the initial digital screen to receiving an offer, within two to three weeks.
Speedway Software Engineer candidate reports ↗Where are the primary engineering teams located?
Many of the core engineering and IT teams are based near the corporate headquarters in Enon, OH, though virtual and hybrid opportunities may exist depending on the specific team and project requirements.
Speedway Software Engineer candidate reports ↗What is the work culture like for engineers at Speedway?
The culture is highly collaborative, practical, and supportive. Teams work closely together to solve real-world operational challenges, and there is a strong emphasis on mentorship, especially for co-ops and entry-level engineers.
Speedway Software Engineer candidate reports ↗What topics does Speedway test in interviews?
Speedway interviews most often cover Stakeholder Management, Time Management, Retail operations management, Marketing Analytics, and Behavioral interview skills. The exact emphasis depends on the specific role you apply for.
Speedway 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.
- 01Speedway 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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