As a Software Engineer at SimilarWeb, you are at the core of a platform that processes massive amounts of digital data to provide global market intelligence. Your work directly influences how the world’s largest companies understand their competitive landscape, consumer behavior, and market trends. You will be tasked with building robust, scalable systems that handle high-throughput data pipelines, ensuring that the insights delivered to our clients are both accurate and lightning-fast. The role demands a high level of technical rigor and a passion for solving complex, data-intensive challenges. Whether you are working on backend infrastructure, distributed systems, or front-end data visualization, you will be part of a team that values innovation and efficiency. You will collaborate closely with product managers and data scientists to turn complex requirements into high-performance production code. This position is ideal for engineers who thrive in a fast-paced environment where the impact of their code is visible and immediate. You will be expected to balance technical excellence with a deep understanding of the business goals, ensuring that the solutions you engineer are not only elegant but also drive the strategic success of. SimilarWeb
Phone Screens
reportedInitial calls to evaluate your background and fit for the role.
What to demonstrate
- Initial calls to evaluate your background and fit for the role
- Depth in System Design
How to prepare
- Be able to walk your CV end to end in two minutes, and say why this company specifically.
- Have your salary expectations, notice period and location constraints ready, and ask for the rest of the loop in writing.
Live Coding Sessions
reportedInteractive coding sessions to assess your technical skills in real-time.
What to demonstrate
- Interactive coding sessions to assess your technical skills in real-time
- Depth in System Design
How to prepare
- Answer aloud and timed: Explain the differences between a HashSet and a List in terms of performance and use cases.
- Answer aloud and timed: How would you implement a custom object to serve as a key in a dictionary?
Project Deep Dives
reportedIn-depth discussions about your past projects to understand your experience.
What to demonstrate
- In-depth discussions about your past projects to understand your experience
- Depth in System Design
How to prepare
- Answer aloud and timed: Given a piece of code, identify and fix potential bugs or performance bottlenecks.
- Answer aloud and timed: Explain the architecture of a feature or system you have worked on in detail.
Algorithmic Challenges
reportedProblem-solving tasks focused on algorithms to test your technical prowess.
What to demonstrate
- Problem-solving tasks focused on algorithms to test your technical prowess
- Depth in System Design
How to prepare
- Answer aloud and timed: How would you implement a long-running process with real-time UI updates in a microservices environment?
- Answer aloud and timed: Design a URL hierarchy parser using a stack-based implementation.
System Design Discussions
reportedConversations about system design to evaluate your architectural thinking.
What to demonstrate
- Conversations about system design to evaluate your architectural thinking
- Depth in System Design
How to prepare
- Answer aloud and timed: How do you approach synchronization problems in a distributed system?
- Answer aloud and timed: Walk us through a complex project you handled, focusing on the challenges you faced and how you overcame them.
Team Member Conversations
reportedInterviews with team members to ensure a mutual fit within the team.
What to demonstrate
- Interviews with team members to ensure a mutual fit within the team
- Depth in System Design
How to prepare
- Answer aloud and timed: Tell us about a time you had a disagreement with a team member or manager; how did you resolve it?
- Answer aloud and timed: Why are you interested in working at SimilarWeb, and how does your background align with our mission?
PracHub editorial advice for the preparation topics above.
Be Clear and Concise
When answering questions, start with the conclusion or the core concept, then provide supporting details.
Ask Clarifying Questions
Never start coding until you are sure you understand the requirements. This shows discipline and prevents wasted effort.
Test Your Work
Always walk through your code with a sample input before declaring it finished.
Own Your Mistakes
If you realize you made a mistake during the interview, acknowledge it and explain how you would fix it. We value honesty and the ability to learn.
Choose a category, try a prompt, then open its approach, worked solution or follow-up when you need it.
Given an array of stock prices, find the maximum profit possible from buying and selling stocks.
Given an array of stock prices, find the maximum profit possible from buying and selling stocks.
Approach
- Restate the input: its shape, its size, and what is guaranteed about it.
- Name the brute-force solution and its complexity before improving on it.
- Choose the data structure from the access pattern, not from familiarity.
- 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?
Implement a solution to find the number of neighboring pairs in a circular array whose sum is an even number.
Implement a solution to find the number of neighboring pairs in a circular array whose sum is an even number.
Approach
- Restate the input: its shape, its size, and what is guaranteed about it.
- Name the brute-force solution and its complexity before improving on it.
- Choose the data structure from the access pattern, not from familiarity.
- 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 differences between a HashSet and a List in terms of performance and use cases.
Explain the differences between a HashSet and a List in terms of performance and use cases.
Approach
- Restate the input: its shape, its size, and what is guaranteed about it.
- Name the brute-force solution and its complexity before improving on it.
- Choose the data structure from the access pattern, not from familiarity.
- 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?
How would you implement a custom object to serve as a key in a dictionary?
How would you implement a custom object to serve as a key in a dictionary?
Approach
- Restate the input: its shape, its size, and what is guaranteed about it.
- Name the brute-force solution and its complexity before improving on it.
- Choose the data structure from the access pattern, not from familiarity.
- 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 piece of code, identify and fix potential bugs or performance bottlenecks.
Given a piece of code, identify and fix potential bugs or performance bottlenecks.
Approach
- Restate the input: its shape, its size, and what is guaranteed about it.
- Name the brute-force solution and its complexity before improving on it.
- Choose the data structure from the access pattern, not from familiarity.
- 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?
Stop tag and share joins from fanning out a page
resource_tag is (resource_id, tag_id) with PK (resource_id, tag_id); resource_share is (resource_id, shared_with_user_id, permission). The tagged-and-shared listing inner-joins resource to both, filters tenant_id, tag_id = ANY($2) and shared_with_user_id = $3, orders by updated_at DESC and takes 50. Pages come back with fewer than 50 distinct resources and the total in the header is far too high. Explain the row multiplication, rewrite both the page query and the count query so each is correct, and name the index each one needs. PostgreSQL 16.
Approach
- Do the arithmetic against the predicates that are actually there. An inner join emits one row per matching child row, and both joins are filtered: tag_id = ANY($2) admits only the requested tags, shared_with_user_id = $3 admits one user's share rows. So a resource holding three of the requested tags and shared with $3 once yields three rows, not one — the multiplier is its count of matching tags times its share rows for that single user, and that second factor is 1 unless the table admits duplicate (resource_id, shared_with_user_id) pairs. LIMIT 50 then limits rows rather than resources, and COUNT(*) counts pairs — the header is the product, not the population.
- Reject DISTINCT as the fix. It deduplicates after the product has been built, so the planner must materialise and sort the fanned-out set before the LIMIT can apply, and it leaves any SUM or AVG in the same select list wrong.
- Rewrite both filters as semi-joins, keeping resource as the only row source: AND EXISTS (SELECT 1 FROM resource_tag rt WHERE rt.resource_id = r.resource_id AND rt.tag_id = ANY($2)) and the same shape against resource_share. A semi-join stops at the first match per resource and preserves the driving index order, so ORDER BY updated_at DESC, resource_id DESC LIMIT 50 still stops after 50 rows.
- Count with the same predicates and no join at all: SELECT count(*) FROM resource r WHERE r.tenant_id = $1 AND r.status = 'active' AND EXISTS (...) AND EXISTS (...). Nothing multiplies a resource, so the number is the population.
Follow-up
- The filter changes from 'any of these tags' to 'all of these tags'. Rewrite it and state what it costs relative to the ANY form.
- A resource can be shared with the same user twice under different permissions. Does your count change, and should it?
Denormalise tenant onto revisions and backfill it live
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
- 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.
- 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.
- 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.
- 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?
Explain the architecture of a feature or system you have worked on in detail.
Explain the architecture of a feature or system you have worked on in detail.
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 would you implement a long-running process with real-time UI updates in a microservices environment?
How would you implement a long-running process with real-time UI updates in a microservices environment?
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?
Design a URL hierarchy parser using a stack-based implementation.
Design a URL hierarchy parser using a stack-based implementation.
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 synchronization problems in a distributed system?
How do you approach synchronization problems in a distributed system?
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?
Edge instances grow 400 MB per hour until the nightly restart
Edge API instances start at 700 MB resident and grow about 400 MB/hour; a nightly rolling restart has hidden it for weeks. Growth continues unchanged when request rate halves overnight, p99 degrades in the last hours before an instance is recycled, and heap used immediately after a forced full GC rises monotonically. The service holds no product state. Name the discriminating measurement that separates the plausible causes, give the most likely cause, and give the fix and how you would verify it.
Approach
- Separate resident memory from live heap first, because they fail differently. Resident size can grow from fragmentation, native buffers or thread stacks while the heap is flat; heap used after a full GC rising monotonically is the measurement that says objects are reachable and not being released. You already have it, so this is retention, not fragmentation, and that closes off half the candidate list.
- Use the rate's independence from traffic as the discriminator. Growth that continues at half the request rate rules out per-request objects that are merely slow to collect and points at a structure that grows with distinct values observed rather than with call volume. Write the candidates that have that property: a metrics registry keyed on a high-cardinality label, an unevicted cache, an interner, a per-key lock map.
- Take two heap snapshots an hour apart and diff by retained size, reading the dominator tree, not by allocation count or instance count. Expect one root holding a map with millions of entries, then follow the reference chain to the code that inserts and never removes. Allocation profilers point at churn, which is the wrong signal here.
- The candidate that fits this service is an observability label carrying an identifier, such as a request path recorded before templating so that /v1/resources/48213 becomes its own metric series. That grows with distinct ids seen, is independent of rate, and explains the late p99 degradation, since GC cost rises with the size of the live set.
Follow-up
- Post-GC heap is now flat but resident size still creeps. What are you looking at, and does it matter?
- How would you have detected this before an OOM, given the nightly restart masked the trend?
Built from the rounds and topics SimilarWeb candidates report.
Prepare, practise & reflect
One practical outcome each day. Spend longer where you need it.
0 / 7 done01Map the SimilarWeb loop
- Write out the reported sequence: Phone Screens, Live Coding Sessions, Project Deep Dives, Algorithmic Challenges, System Design Discussions, Team Member Conversations.
- 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 6 reported rounds, with the weakest marked.
02Work System Design
- Spend the session on System Design, which SimilarWeb candidates report being tested on.
- Write one worked example in System Design and time yourself on it.
Deliverable: One timed worked example in System Design.
03Work LRU Cache
- Spend the session on LRU Cache, which SimilarWeb candidates report being tested on.
- Write one worked example in LRU Cache and time yourself on it.
Deliverable: One timed worked example in LRU Cache.
04Work Data Structures
- Spend the session on Data Structures, which SimilarWeb 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.
05Answer out loud: Technical & Algorithmic Foundations
- Answer aloud, timed: Given an array of stock prices, find the maximum profit possible from buying and selling stocks.
- Answer aloud, timed: Implement a solution to find the number of neighboring pairs in a circular array whose sum is an even number.
Deliverable: Spoken answers to 2 reported Technical & Algorithmic Foundations question(s), under time.
06Answer out loud: System Design & Architecture
- Answer aloud, timed: Explain the architecture of a feature or system you have worked on in detail.
- Answer aloud, timed: How would you implement a long-running process with real-time UI updates in a microservices environment?
Deliverable: Spoken answers to 2 reported System Design & Architecture question(s), under time.
07Answer out loud: Behavioral & Professional Background
- Answer aloud, timed: Walk us through a complex project you handled, focusing on the challenges you faced and how you overcame them.
- Answer aloud, timed: Tell us about a time you had a disagreement with a team member or manager; how did you resolve it?
Deliverable: Spoken answers to 2 reported Behavioral & Professional Background 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.
Walk us through a complex project you handled, focusing on the challenges you faced and how you overcame them.
Walk us through a complex project you handled, focusing on the challenges you faced and how you overcame them.
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 a disagreement with a team member or manager; how did you resolve it?
Tell us about a time you had a disagreement with a team member or manager; 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?
Why are you interested in working at SimilarWeb, and how does your background align with our mission?
Why are you interested in working at SimilarWeb, and how does your background align with our mission?
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
Walk us through a complex project you handled, focusing on the challenges you faced and how you overcame them.
- 02
Tell us about a time you had a disagreement with a team member or manager; how did you resolve it?
- 03
Why are you interested in working at SimilarWeb, and how does your background align with our mission?
How difficult are the technical interviews?
The difficulty is calibrated to the seniority of the role. You should expect a mix of standard algorithmic questions and role-specific technical scenarios that test your practical knowledge.
SimilarWeb Software Engineer candidate reports ↗What is the best way to prepare for the live coding sessions?
Practice solving problems on a whiteboard or a shared document without an IDE. Focus on verbalizing your thought process as you code, as this is a key part of how we evaluate your problem-solving style.
SimilarWeb Software Engineer candidate reports ↗How long does the process usually take?
While it can vary, many candidates move through the process in about 3 to 4 weeks. We aim to keep the process efficient and responsive.
SimilarWeb Software Engineer candidate reports ↗Is there a home assignment?
Some roles include a home assignment, which is designed to see how you approach a real-world task over a longer period. Treat this as a chance to show your best work, including testing and documentation.
SimilarWeb Software Engineer candidate reports ↗What topics does SimilarWeb test in interviews?
SimilarWeb interviews most often cover Stakeholder Management, Technical Communication, Python, System Design, and Algorithms. The exact emphasis depends on the specific role you apply for.
SimilarWeb 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.
- 01SimilarWeb 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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