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Druva Software Engineer Interview Guide

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

The 60-second brief

As a Software Engineer at Druva, you are at the core of building and scaling the industry’s leading cloud-native data protection and management platform. Your work directly impacts how global enterprises secure, protect, and recover their most critical data. You will be responsible for designing resilient systems, optimizing performance for large-scale distributed environments, and ensuring that our data-handling infrastructure remains both secure and highly available. This role requires a blend of deep technical rigor and an ability to think about system-wide architecture. You will collaborate with cross-functional teams to solve complex challenges related to data deduplication, cloud storage optimization, and high-concurrency processing.

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

Focus areas

  • Data Structures
  • Algorithms
  • JavaScript

The Druva interview process

Druva candidates report 3 rounds over 3-5 weeks. The stages below are what candidates describe, not a published process.

Online Assessment

Initial coding test to gauge baseline proficiency.

What to demonstrate

  • Initial coding test to gauge baseline proficiency
  • Depth in Data Structures

How to prepare

  • Answer aloud and timed: How would you implement a stack using only two queues?
  • Answer aloud and timed: Find the longest palindromic substring within a given string.

Technical Rounds

Series of telephonic or virtual technical interviews.

What to demonstrate

  • Series of telephonic or virtual technical interviews
  • Depth in Data Structures

How to prepare

  • Answer aloud and timed: Design an algorithm to detect a cycle in a linked list and find the starting node.
  • Answer aloud and timed: Given an array of integers, find the maximum profit from buying and selling stocks.

Onsite/Video Interviews

Interviews with engineering managers, senior developers, and occasionally leadership.

What to demonstrate

  • Interviews with engineering managers, senior developers, and occasionally leadership
  • Depth in Data Structures

How to prepare

  • Answer aloud and timed: Explain the time and space complexity of your solution for a sliding window problem.
  • Answer aloud and timed: Explain what happens behind the scenes when you type a URL into a browser and press enter.

Where candidates lose points

Prioritize Clarity

When writing pseudocode or code on a whiteboard, focus on readability. Use meaningful variable names and organize your logic logically.

Own Your Resume

Expect deep-dive questions on any project you list. If you claim to have used a specific technology, be ready to discuss its internal workings and why you chose it over alternatives.

Prepare for "Curveballs

Interviewers may introduce new constraints mid-problem. Do not get flustered; treat these as opportunities to demonstrate your flexibility and analytical skills.

Be Professional

Despite varying reports on communication speed, always maintain a high level of professionalism in your emails and interviews. It reflects your maturity as a candidate.

Questions & practice

How would you implement a stack using only two queues?

Medium · Data Structures and Algorithms

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?

Find the longest palindromic substring within a given string.

Medium · Data Structures and Algorithms

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 an array of integers, find the maximum profit from buying and selling stocks.

Medium · Data Structures and Algorithms

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?

Explain the time and space complexity of your solution for a sliding window problem.

Medium · Data Structures and Algorithms

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?

Compare and contrast Mutexes and Semaphores in the context of multi-threaded applications.

Medium · Operating Systems and Networking

Approach

  1. Say what the runtime actually does before reasoning about the code.
  2. Name what is shared across threads and what owns each piece of state.
  3. Identify the window where an invariant is briefly untrue.
  4. Distinguish a value from a reference to it, and say which one you handed out.

Follow-up

  • What happens if two callers reach this at the same time?
  • Where could this allocate more than you expect?

How does Virtual Memory work, and what is the concept of thrashing?

Medium · Operating Systems and Networking

Approach

  1. Say what the runtime actually does before reasoning about the code.
  2. Name what is shared across threads and what owns each piece of state.
  3. Identify the window where an invariant is briefly untrue.
  4. Distinguish a value from a reference to it, and say which one you handed out.

Follow-up

  • What happens if two callers reach this at the same time?
  • Where could this allocate more than you expect?

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?

Write the update path that detects a concurrent edit

Medium · optimistic concurrency · transactional outbox · audit history

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

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

Design an algorithm to detect a cycle in a linked list and find the starting node.

Medium · Data Structures and Algorithms

Approach

  1. Fix the scope first: who calls this, how often, and what they do when it fails.
  2. Name the read and write paths separately; they rarely have the same bottleneck.
  3. Choose a partition key and say what query it makes expensive.
  4. State the consistency you need, and where you are willing to be stale.

Follow-up

  • What breaks first when traffic grows ten times?
  • How does this behave when that dependency is down for an hour?

Explain what happens behind the scenes when you type a URL into a browser and press enter.

Medium · Operating Systems and Networking

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?

Describe the difference between TCP and UDP and when you would choose one over the other.

Medium · Operating Systems and Networking

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?

Design a URL shortening service that can handle high traffic.

Medium · System Design

Approach

  1. Fix the scope first: who calls this, how often, and what they do when it fails.
  2. Name the read and write paths separately; they rarely have the same bottleneck.
  3. Choose a partition key and say what query it makes expensive.
  4. 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 would you design a distributed file system that guarantees data consistency?

Medium · System Design

Approach

  1. Fix the scope first: who calls this, how often, and what they do when it fails.
  2. Name the read and write paths separately; they rarely have the same bottleneck.
  3. Choose a partition key and say what query it makes expensive.
  4. State the consistency you need, and where you are willing to be stale.

Follow-up

  • What breaks first when traffic grows ten times?
  • How does this behave when that dependency is down for an hour?

Explain how to handle duplicate data in a high-velocity streaming object pipeline.

Medium · System Design

Approach

  1. Fix the scope first: who calls this, how often, and what they do when it fails.
  2. Name the read and write paths separately; they rarely have the same bottleneck.
  3. Choose a partition key and say what query it makes expensive.
  4. 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?

Describe how you would design a multi-threaded directory walker.

Medium · System Design

Approach

  1. Fix the scope first: who calls this, how often, and what they do when it fails.
  2. Name the read and write paths separately; they rarely have the same bottleneck.
  3. Choose a partition key and say what query it makes expensive.
  4. 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 debug a network connectivity issue in a distributed environment?

Medium · Operating Systems and Networking

Approach

  1. Establish what changed and when, before forming any theory.
  2. Pick a bisection that eliminates candidates whichever way it turns out.
  3. Check the instrumentation before believing the symptom.
  4. 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?

Suggested practice checklist

Built from the rounds and topics Druva candidates report.

Day 1 — Map the Druva loop

  • Write out the reported sequence: Online Assessment, Technical Rounds, Onsite/Video 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.

Day 2 — Work Data Structures

  • Spend the session on Data Structures, which Druva candidates report being tested on.
  • Write one worked example in Data Structures and time yourself on it.

Deliverable: One timed worked example in Data Structures.

Day 3 — Work Algorithms

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

Deliverable: One timed worked example in Algorithms.

Day 4 — Work JavaScript

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

Deliverable: One timed worked example in JavaScript.

Day 5 — Answer out loud: Data Structures and Algorithms

  • Answer aloud, timed: How would you implement a stack using only two queues?
  • Answer aloud, timed: Find the longest palindromic substring within a given string.

Deliverable: Spoken answers to 2 reported Data Structures and Algorithms question(s), under time.

Day 6 — Answer out loud: Operating Systems and Networking

  • Answer aloud, timed: Explain what happens behind the scenes when you type a URL into a browser and press enter.
  • Answer aloud, timed: Compare and contrast Mutexes and Semaphores in the context of multi-threaded applications.

Deliverable: Spoken answers to 2 reported Operating Systems and Networking question(s), under time.

Day 7 — Answer out loud: System Design

  • Answer aloud, timed: Design a URL shortening service that can handle high traffic.
  • Answer aloud, timed: How would you design a distributed file system that guarantees data consistency?

Deliverable: Spoken answers to 2 reported System Design question(s), under time.

Behavioural preparation

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

Walk me through the most challenging technical project you have led.

Medium · Project Experience and Behavioral

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?

How do you handle disagreements with teammates regarding technical implementation?

Medium · Project Experience and Behavioral

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?

Tell me about a time you had to optimize a piece of code that was performing poorly in production.

Medium · Project Experience and Behavioral

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?