A Software Engineer at Odeko plays a critical role in empowering independent cafes and coffee shops to compete with multinational chains. By building and maintaining the technology that powers mobile ordering, supply chain logistics, and inventory management, engineers directly impact the daily operations of thousands of small businesses. The work is highly tangible; code shipped to production directly influences how fresh inventory is routed, how orders are processed, and how small business owners manage their margins. The engineering team at Odeko tackles complex, real-world challenges that span across e-commerce, predictive inventory, and supply chain logistics. As a Software Engineer, you will contribute to systems that require high reliability, seamless user experiences, and efficient data processing. Whether optimizing the routing of delivery trucks or refining the checkout flow for a neighborhood cafe, your contributions will scale a platform that bridges digital convenience with physical operations. This role is ideal for engineers who thrive in collaborative, mission-driven environments. values practical problem-solving, clean code, and a strong sense of empathy for the end user. You will have the opportunity to take ownership of features from conception to deployment, collaborating closely with product managers, designers, and operations teams to build an ecosystem that keeps local communities thriving. Odeko
Initial Conversation
reportedDiscuss your background, career goals, and the company's mission with the hiring manager or CTO.
What to demonstrate
- Discuss your background, career goals, and the company's mission with the hiring manager or CTO
- Depth in Coding Challenges
How to prepare
- Answer aloud and timed: Walk us through your implementation of the take-home challenge and explain the reasoning behind your architectural choices.
- Answer aloud and timed: If you had more time, what trade-offs would you revisit in your code, and how would you restructure your solution?
Take-Home Coding Assignment
reportedComplete a coding assignment delivered via GitHub to simulate real-world tasks.
What to demonstrate
- Complete a coding assignment delivered via GitHub to simulate real-world tasks
- Depth in Coding Challenges
How to prepare
- Answer aloud and timed: How does your solution handle edge cases, and how would you scale this implementation if the data volume increased tenfold?
- Answer aloud and timed: Why did you choose this specific data structure or library over other available alternatives?
Technical Walkthrough
reportedParticipate in a session with two engineers to discuss your code and design choices.
What to demonstrate
- Participate in a session with two engineers to discuss your code and design choices
- Depth in Coding Challenges
How to prepare
- Answer aloud and timed: Tell us about a complex technical project you completed in a past role, focusing on the architectural decisions you made.
- Answer aloud and timed: Describe a time when you had to debug a difficult production issue. What was your process, and what did you learn?
Behavioral Interview
reportedAnswer situational behavioral questions and discuss alignment with Odeko's core values.
What to demonstrate
- Answer situational behavioral questions and discuss alignment with Odeko's core values
- Depth in Coding Challenges
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 interview above and write down what you would ask to confirm before it.
Final Wrap-Up
reportedHave a final conversation with the CTO or engineering leadership to align on expectations.
What to demonstrate
- Have a final conversation with the CTO or engineering leadership to align on expectations
- Depth in Coding Challenges
How to prepare
- Answer aloud and timed: Why do you want to work at Odeko, and how do you align with our mission to support independent small businesses?
- Answer aloud and timed: Describe a situation where you had a disagreement with a peer or stakeholder. How did you resolve it?
PracHub editorial advice for the preparation topics above.
Prioritize Clean Code Over Clever Code
During the take-home assignment, focus on readability, clear naming conventions, and robust testing. The engineering team values maintainability far more than overly complex, clever solutions.
Be Ready to Discuss Trade-offs
No system or solution is perfect. When walking through your code, proactively point out the limitations of your implementation and explain what you would improve if you had more time.
Understand the Business Domain
Take the time to understand Odeko business model. Knowing how they serve local coffee shops and manage physical supply chains will help you contextualize your technical answers and demonstrate genuine interest.
Showcase Your Collaborative Style
Throughout the behavioral and technical discussions, highlight how you collaborate with others, receive feedback, and mentor team members. Humility and teamwork are highly valued attributes.
Choose a category, try a prompt, then open its approach, worked solution or follow-up when you need it.
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?
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?
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?
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 us through your implementation of the take-home challenge and explain the reasoning behind your architect
Walk us through your implementation of the take-home challenge and explain the reasoning behind your architectural choices.
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?
If you had more time, what trade-offs would you revisit in your code, and how would you restructure your solut
If you had more time, what trade-offs would you revisit in your code, and how would you restructure your solution?
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 does your solution handle edge cases, and how would you scale this implementation if the data volume incre
How does your solution handle edge cases, and how would you scale this implementation if the data volume increased tenfold?
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?
Why did you choose this specific data structure or library over other available alternatives?
Why did you choose this specific data structure or library over other available alternatives?
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?
Tell us about a complex technical project you completed in a past role, focusing on the architectural decision
Tell us about a complex technical project you completed in a past role, focusing on the architectural decisions you made.
Approach
- Fix the scope first: who calls this, how often, and what they do when it fails.
- Name the read and write paths separately; they rarely have the same bottleneck.
- Choose a partition key and say what query it makes expensive.
- State the consistency you need, and where you are willing to be stale.
Follow-up
- What breaks first when traffic grows ten times?
- How does this behave when that dependency is down for an hour?
How do you approach testing in your daily workflow, and how do you ensure code quality before deployment?
How do you approach testing in your daily workflow, and how do you ensure code quality before deployment?
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?
Describe a time when you had to debug a difficult production issue. What was your process, and what did you le
Describe a time when you had to debug a difficult production issue. What was your process, and what did you learn?
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 Odeko candidates report.
Prepare, practise & reflect
One practical outcome each day. Spend longer where you need it.
0 / 7 done01Map the Odeko loop
- Write out the reported sequence: Initial Conversation, Take-Home Coding Assignment, Technical Walkthrough, Behavioral Interview, Final Wrap-Up.
- 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 5 reported rounds, with the weakest marked.
02Work Coding Challenges
- Spend the session on Coding Challenges, which Odeko candidates report being tested on.
- Write one worked example in Coding Challenges and time yourself on it.
Deliverable: One timed worked example in Coding Challenges.
03Work Code Walkthrough / Code Review Discussion
- Spend the session on Code Walkthrough / Code Review Discussion, which Odeko candidates report being tested on.
- Write one worked example in Code Walkthrough / Code Review Discussion and time yourself on it.
Deliverable: One timed worked example in Code Walkthrough / Code Review Discussion.
04Work Take-Home Assignments
- Spend the session on Take-Home Assignments, which Odeko candidates report being tested on.
- Write one worked example in Take-Home Assignments and time yourself on it.
Deliverable: One timed worked example in Take-Home Assignments.
05Answer out loud: Code Walkthrough & Design Decisions
- Answer aloud, timed: Walk us through your implementation of the take-home challenge and explain the reasoning behind your architectural choices.
- Answer aloud, timed: If you had more time, what trade-offs would you revisit in your code, and how would you restructure your solution?
Deliverable: Spoken answers to 2 reported Code Walkthrough & Design Decisions question(s), under time.
06Answer out loud: Technical Experience & Past Projects
- Answer aloud, timed: Tell us about a complex technical project you completed in a past role, focusing on the architectural decisions you made.
- Answer aloud, timed: Describe a time when you had to debug a difficult production issue. What was your process, and what did you learn?
Deliverable: Spoken answers to 2 reported Technical Experience & Past Projects question(s), under time.
07Answer out loud: Behavioral & Core Values
- Answer aloud, timed: Why do you want to work at Odeko, and how do you align with our mission to support independent small businesses?
- Answer aloud, timed: Describe a situation where you had a disagreement with a peer or stakeholder. How did you resolve it?
Deliverable: Spoken answers to 2 reported Behavioral & Core Values 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.
Can you discuss a time when you had to make a significant technical trade-off to meet a tight business deadlin
Can you discuss a time when you had to make a significant technical trade-off to meet a tight business deadline?
Approach
- Pick a story where you made the decision, not one where you watched it.
- State the situation in two sentences and spend the rest on the reasoning.
- Give the blast radius: what could have broken, and what you measured.
- Name the disagreement and how you resolved it with evidence.
Follow-up
- What would you do differently if you ran that again?
- How did you know your change caused the improvement?
Why do you want to work at Odeko, and how do you align with our mission to support independent small businesse
Why do you want to work at Odeko, and how do you align with our mission to support independent small businesses?
Approach
- Pick a story where you made the decision, not one where you watched it.
- State the situation in two sentences and spend the rest on the reasoning.
- Give the blast radius: what could have broken, and what you measured.
- Name the disagreement and how you resolved it with evidence.
Follow-up
- What would you do differently if you ran that again?
- How did you know your change caused the improvement?
Describe a situation where you had a disagreement with a peer or stakeholder. How did you resolve it?
Describe a situation where you had a disagreement with a peer or stakeholder. 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 handle constructive criticism or feedback on your code during peer reviews?
How do you handle constructive criticism or feedback on your code during peer 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?
Tell us about a time you had to learn a new technology or domain quickly to solve a pressing problem.
Tell us about a time you had to learn a new technology or domain quickly to solve a pressing problem.
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
Can you discuss a time when you had to make a significant technical trade-off to meet a tight business deadline?
- 02
Why do you want to work at Odeko, and how do you align with our mission to support independent small businesses?
- 03
Describe a situation where you had a disagreement with a peer or stakeholder. How did you resolve it?
- 04
How do you handle constructive criticism or feedback on your code during peer reviews?
How difficult is the Software Engineer interview process at Odeko?
The process is generally rated as average in difficulty. Odeko focuses on practical engineering skills through a take-home assignment rather than complex algorithmic puzzles or whiteboard coding, making the evaluation feel more aligned with daily engineering work.
Odeko Software Engineer candidate reports ↗How long does the take-home assignment typically take?
The take-home task is designed to be completed in a few hours. Odeko values your personal time, so they focus on a scoped problem that allows you to demonstrate code quality, testing, and design decisions without requiring days of work.
Odeko Software Engineer candidate reports ↗What is the company culture like within the engineering team?
The engineering culture at Odeko is highly collaborative, mission-driven, and friendly. Team members are passionate about small businesses, and there is a strong emphasis on mutual support, constructive feedback, and continuous learning.
Odeko Software Engineer candidate reports ↗What is the typical timeline from the initial screen to an offer?
The entire process usually takes between two to three weeks. However, because the stages are thorough and involve multiple team members (including engineering leadership and the CTO), scheduling can sometimes extend the timeline slightly.
Odeko Software Engineer candidate reports ↗What topics does Odeko test in interviews?
Odeko interviews most often cover Coding Challenges, Code Walkthrough / Code Review Discussion, Take-Home Assignments, Explaining Implementation Reasoning, and General Engineering Questions. The exact emphasis depends on the specific role you apply for.
Odeko 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.
- 01Odeko 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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