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Zestiot Software Engineer Interview Guide

Zestiot Software Engineer interview guide: reported rounds, questions and how candidates describe the process.

The 60-second brief

As a Software Engineer at Zestiot, you serve as a core architect of the solutions that drive our platform’s value. This role is not merely about writing code; it is about solving complex, real-world problems that directly impact our customers. You will work within a collaborative environment where your ability to translate ambiguous requirements into clean, scalable, and efficient software is paramount. The work you do here is critical to our product's reliability and innovation. You will be expected to engage deeply with the entire development lifecycle, from initial conceptualization and system design to implementation and iterative improvement. At Zestiot, we value engineers who possess a deep curiosity, a strong grasp of technical fundamentals, and the ability to articulate their thought process clearly while navigating technical challenges alongside their team.

This guide is scoped to a Software Engineer candidate at Zestiot.

Focus areas

  • React.js
  • Problem Solving Approach
  • Technical Interviewing

Where to focus your preparation

No round sequence has been reported for Zestiot. Confirm the format with your recruiter.

Preparation focus

No round sequence has been reported for this company, so confirm the format with your recruiter and work the reported questions below.

What to demonstrate

  • Breadth across the topics this company reports testing
  • Whether you confirm the format before preparing for it

How to prepare

  • Ask the recruiter for the sequence, the duration of each stage and whether you will be writing code
  • Work the reported questions below and time yourself

Where candidates lose points

Think out loud

This is the most crucial piece of advice. If you go silent while solving a problem, we cannot evaluate your reasoning.

Clarify the scope

Before jumping into a solution, ask clarifying questions to ensure you understand the constraints and edge cases.

Own your past work

Be prepared to discuss the specific technical challenges you faced in your previous roles and how you contributed to the final outcome.

Stay calm under pressure

If you get stuck, take a breath and communicate your current thought process to the interviewer; they are there to help guide you.

Questions & practice

Walk me through how you would approach designing a feature from scratch.

Medium · Problem Solving and Methodology

Approach

  1. Restate the input: its shape, its size, and what is guaranteed about it.
  2. Name the brute-force solution and its complexity before improving on it.
  3. Choose the data structure from the access pattern, not from familiarity.
  4. 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?

If a system is performing poorly under load, what steps do you take to identify the bottleneck?

Medium · Problem Solving and Methodology

Approach

  1. Restate the input: its shape, its size, and what is guaranteed about it.
  2. Name the brute-force solution and its complexity before improving on it.
  3. Choose the data structure from the access pattern, not from familiarity.
  4. 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?

Describe a situation where you had to compromise on a technical implementation; how did you arrive at that dec

Medium · Problem Solving and Methodology

Describe a situation where you had to compromise on a technical implementation; how did you arrive at that decision?

Approach

  1. Restate the input: its shape, its size, and what is guaranteed about it.
  2. Name the brute-force solution and its complexity before improving on it.
  3. Choose the data structure from the access pattern, not from familiarity.
  4. 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?

Given a scenario where requirements are changing mid-sprint, how do you adjust your development strategy?

Medium · Problem Solving and Methodology

Approach

  1. Restate the input: its shape, its size, and what is guaranteed about it.
  2. Name the brute-force solution and its complexity before improving on it.
  3. Choose the data structure from the access pattern, not from familiarity.
  4. 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?

Replace offset paging on the resource feed with keyset

Easy · keyset pagination · composite index · sort order

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

  1. 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.
  2. 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.
  3. 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.
  4. 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?

Denormalise tenant onto revisions and backfill it live

Hard · denormalisation · online migration · backfill

resource_revision (revision_id, resource_id, version, actor_user_id, change_kind, patch, request_id, created_at) has 400M rows and no tenant column; tenant_id lives only on resource. Two reads need it: a tenant-scoped audit feed ordered by created_at DESC, and an offboarding purge. Both join back to resource today. Justify adding tenant_id to resource_revision against those two reads, name the anomaly the copy introduces and the constraint that prevents it, then give the ordered migration for a live table taking 1.2k writes/second — the lock each step takes, how the backfill is batched, and where each step stops being reversible. PostgreSQL 16.

Approach

  1. Justify from the access path rather than from taste. Without the column, the audit feed either scans resource_revision by created_at and discards other tenants' rows, or resolves the tenant's resource_ids first and probes with them — both proportional to the tenant's whole history rather than to one page. With (tenant_id, created_at DESC, revision_id DESC) it is a seek that stops at 50 rows, and the purge becomes a ranged delete instead of a join.
  2. Name the cost exactly: a second copy of a fact can disagree with the first. Make the disagreement unwritable rather than documented — add UNIQUE (resource_id, tenant_id) on resource so it can serve as a foreign-key target, then FOREIGN KEY (resource_id, tenant_id) REFERENCES resource (resource_id, tenant_id) on the revision table. A revision can then only ever carry its parent's tenant.
  3. Step one, expand: ALTER TABLE resource_revision ADD COLUMN tenant_id BIGINT NULL, with no default, so it is a catalogue change and no rewrite. It still needs ACCESS EXCLUSIVE for an instant, and that instant queues behind the longest open transaction on the table while every later query queues behind it — set lock_timeout to 2s and retry rather than wait.
  4. Step two, dual-write: deploy the writer that populates tenant_id on every new revision while reads still use the join. Reversible by redeploying the previous build, because nothing reads the column yet.

Follow-up

  • The backfill is half finished and a rollback is required. What state is the table in, and what does the previous build do with a half-populated column?
  • How do you verify the backfill actually finished, given rows are still being inserted while it runs?

Can you explain the difference between class components and functional components in React.js?

Medium · Technical and Domain Knowledge

Approach

  1. Clarify what is being asked and what a complete answer contains.
  2. State your assumptions explicitly before working the problem.
  3. Say what you would check first and why it is the highest-information step.
  4. 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 the component lifecycle work, and when would you use specific lifecycle methods?

Medium · Technical and Domain Knowledge

Approach

  1. Clarify what is being asked and what a complete answer contains.
  2. State your assumptions explicitly before working the problem.
  3. Say what you would check first and why it is the highest-information step.
  4. 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 JSX, and how does it function within the React ecosystem?

Medium · Technical and Domain Knowledge

Approach

  1. Clarify what is being asked and what a complete answer contains.
  2. State your assumptions explicitly before working the problem.
  3. Say what you would check first and why it is the highest-information step.
  4. Work from the requirement backwards to the design.

Follow-up

  • What assumption would you test first?
  • How would you know your answer was wrong?

How do you manage state effectively in a large-scale React application?

Medium · Technical and Domain Knowledge

Approach

  1. Clarify what is being asked and what a complete answer contains.
  2. State your assumptions explicitly before working the problem.
  3. Say what you would check first and why it is the highest-information step.
  4. 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 describe a challenging bug you encountered in a front-end project and your step-by-step approach to fi

Medium · Technical and Domain Knowledge

Can you describe a challenging bug you encountered in a front-end project and your step-by-step approach to fixing it?

Approach

  1. Clarify what is being asked and what a complete answer contains.
  2. State your assumptions explicitly before working the problem.
  3. Say what you would check first and why it is the highest-information step.
  4. Work from the requirement backwards to the design.

Follow-up

  • What assumption would you test first?
  • How would you know your answer was wrong?

One log partition stops advancing while the others drain

Easy · poison message · head-of-line blocking · consumer lag

Search results for a subset of tenants are hours stale; the rest are current. The projection consumer reports lag of zero on 15 of 16 partitions and 400,000 on one. Its error rate is flat and its CPU is idle. outbox_event has no pending rows older than a second, so the relay has published everything it holds. Identify the mechanism, give the ordered checks, and state what you do in the first ten minutes versus what you change permanently.

Approach

  1. Read the lag distribution first. A slow consumer lags everywhere; zero on fifteen partitions and 400,000 on one is not throughput. Idle CPU on the stuck partition means the consumer is not advancing its offset at all, which points at one message it cannot get past rather than at a rate problem.
  2. Exonerate the producer before touching the consumer. No pending outbox rows older than a second means the relay published, so the event exists in the log. This separates never sent from sent and never applied, which are different code paths and usually different owners.
  3. Read the message at the stuck offset and the handler's log lines for its event_id. A flat error rate with no progress has two explanations and you must distinguish them: the handler is throwing and the retry loop is swallowing it, or the handler is blocking on something and never returning. Idle CPU with no error lines favours the second.
  4. Mitigate before diagnosing further. Move the offending event to a dead-letter store and commit the offset past it. Adding consumers does nothing here, because a partition is consumed by exactly one member of the group, and the blast radius is every aggregate hashed to that partition, not only the aggregate that produced the bad event.

Follow-up

  • The dead-lettered event carried aggregate_version 7 and the projection had applied 6. What must the replay do differently if 8 and 9 landed in the meantime?
  • How do you show staleness to the user while the partition is behind, given the API already returns the projection's watermark?

Suggested practice checklist

Built from the topics and questions Zestiot candidates report; no round sequence has been reported.

Day 1 — Establish the Zestiot format

  • No round sequence has been reported, so ask your recruiter for the sequence, the duration of each stage and whether you will write code.

Deliverable: A written reply from your recruiter confirming the format.

Day 2 — Work React.js

  • Spend the session on React.js, which Zestiot candidates report being tested on.
  • Write one worked example in React.js and time yourself on it.

Deliverable: One timed worked example in React.js.

Day 3 — Work Problem Solving Approach

  • Spend the session on Problem Solving Approach, which Zestiot candidates report being tested on.
  • Write one worked example in Problem Solving Approach and time yourself on it.

Deliverable: One timed worked example in Problem Solving Approach.

Day 4 — Work Technical Interviewing

  • Spend the session on Technical Interviewing, which Zestiot candidates report being tested on.
  • Write one worked example in Technical Interviewing and time yourself on it.

Deliverable: One timed worked example in Technical Interviewing.

Day 5 — Answer out loud: Technical and Domain Knowledge

  • Answer aloud, timed: Can you explain the difference between class components and functional components in React.js?
  • Answer aloud, timed: How does the component lifecycle work, and when would you use specific lifecycle methods?

Deliverable: Spoken answers to 2 reported Technical and Domain Knowledge question(s), under time.

Day 6 — Answer out loud: Problem Solving and Methodology

  • Answer aloud, timed: Walk me through how you would approach designing a feature from scratch.
  • Answer aloud, timed: If a system is performing poorly under load, what steps do you take to identify the bottleneck?

Deliverable: Spoken answers to 2 reported Problem Solving and Methodology question(s), under time.

Day 7 — Dry run for Zestiot

  • 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.

Behavioural preparation

Behavioural rounds judge the decision you made and what it cost.

How do you approach code reviews, both as a reviewer and as the person being reviewed?

Medium · Problem Solving and Methodology

Approach

  1. Pick a story where you made the decision, not one where you watched it.
  2. State the situation in two sentences and spend the rest on the reasoning.
  3. Give the blast radius: what could have broken, and what you measured.
  4. 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?

Reverse your own decision and price the reversal

Medium · reversibility · measurement · migrations

Describe a technical decision you made and later reversed. Pick one that cost something: a service you split and merged back, a cache you added and removed, an index you created that pushed the planner onto a worse plan, a projection you rebuilt from scratch. State what you believed when you decided, the measurement that changed your mind, how long the wrong version ran in production, and what the reversal cost in migrations, dual writes, and a deprecation window for callers you did not own.

Approach

  1. State the original rationale without irony, in the version you would still defend given what was known then. If it is not defensible, the story is about carelessness rather than judgement, and a different example serves you better.
  2. Give the measurement that moved with a before and after: the p99 that did not improve, the cache hit rate that sat at 40%, the plan that flipped to a sequential scan once the table passed a size you can name.
  3. Cost the reversal in steps, not adjectives: expand-and-contract deploys, the dual-write window, the callers who had to be notified, the rows already written in the wrong shape that had to be backfilled or abandoned.
  4. Distinguish reversal from rewrite by naming what you kept. Most good reversals preserve the schema or the interface and undo one decision inside it, which is also why they were affordable.

Follow-up

  • What in that decision was irreversible, and did you know it was irreversible when you made it?
  • How did you tell the people who had already built on top of the original decision?

Argue against a design, lose, and commit anyway

Medium · disagreement · service boundaries · decision records

Describe a design you argued against and lost. State the failure you predicted as a named mechanism, not a feeling about complexity: two services that would need one transaction, a projection with no rebuild path, a write path with no idempotency key. Say what evidence you brought, what the decision maker weighed instead, and what you did after the decision was made: what you instrumented, what you wrote down, and whether the prediction came true. Five minutes.

Approach

  1. State the prediction in falsifiable form up front: the mechanism, the condition that triggers it, and the observable outcome. A prediction that cannot be checked also cannot be credited to you later.
  2. Show the evidence you had at the time and label each piece honestly as measured, analogous, or intuition. Keeping the intuition is fine; disguising it as data is the thing that erodes your standing in the next argument.
  3. Represent the opposing case at full strength, including the constraint you did not control: a fixed date, a team boundary, or the fact that the decision was cheap to reverse and yours was not.
  4. Make disagree-and-commit concrete. Name the artefact you left behind so the prediction could be settled without you: the alert and its threshold, the counter on the dashboard, the decision note that recorded the trade-off and the condition that would revisit it.

Follow-up

  • What threshold on that alert would have proved you right, and did anyone ever look at it?
  • If the same proposal arrived tomorrow with the same deadline, would you argue it the same way?