At Solarsquare, a Software Engineer does not just write code; they build the technology stack that powers India's clean energy transition. As one of the country's leading residential solar platforms, the company relies heavily on its engineering team to solve complex, real-world problems. The software you design and maintain directly impacts how solar systems are designed, installed, monitored, and serviced across thousands of homes and commercial spaces. The engineering team is tasked with creating seamless digital experiences for consumers, optimizing complex supply chains, and automating field operations. From building IoT-enabled monitoring systems that track solar energy generation in real time to designing robust backend systems that coordinate logistics and installations, your work will sit at the intersection of physical hardware and highly scalable cloud software. This role is highly critical because Solarsquare is scaling rapidly. The systems you build must be resilient, highly performant, and capable of handling complex data models. If you are passionate about writing clean, efficient code and want to see your work drive tangible, sustainable environmental impact, this position offers a unique and deeply rewarding technical challenge.
Initial Screening
reportedThe process begins with an initial screening round to assess basic qualifications.
What to demonstrate
- The process begins with an initial screening round to assess basic qualifications
- Depth in RESTful APIs
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.
Technical Discussions
reportedCandidates engage in deep-dive technical discussions to evaluate their knowledge and skills.
What to demonstrate
- Candidates engage in deep-dive technical discussions to evaluate their knowledge and skills
- Depth in RESTful APIs
How to prepare
- Answer aloud and timed: What are the differences between using promises, async/await, and callbacks, and when would you choose one over the other?
- Answer aloud and timed: How would you structure a Node.js application to ensure high modularity and ease of testing?
Hands-on Coding
reportedCandidates participate in hands-on coding exercises to demonstrate their real-world development skills.
What to demonstrate
- Candidates participate in hands-on coding exercises to demonstrate their real-world development skills
- Depth in RESTful APIs
How to prepare
- Answer aloud and timed: Explain how you would optimize a slow-running Node.js process that is bottlenecked by CPU-intensive tasks.
- Answer aloud and timed: Design a MongoDB database schema for a solar installation tracking system, ensuring relationships between customers, physical components, and installation teams are optimized.
PracHub editorial advice for the preparation topics above.
Master Vanilla Node.js
Do not rely solely on frameworks. Be comfortable writing clean, structured code using core Node.js modules and standard Javascript.
Explain Your Schema Trade-offs
When designing database schemas, explicitly state why you chose to embed or reference documents. Showing that you understand the performance implications of your design is highly impressive to the engineering team.
Naming no test cases at all
State what you would test before being asked: empty input, a single element, all elements equal, the maximum permitted size, and the input that exercises the branch you just wrote. It costs thirty seconds and is much of what separates someone who has shipped code from someone who has only solved puzzles.
Choose a category, try a prompt, then open its approach, worked solution or follow-up when you need it.
Explain the Node.js event loop and how it handles asynchronous operations under heavy I/O loads.
Explain the Node.js event loop and how it handles asynchronous operations under heavy I/O loads.
Approach
- Say what the runtime actually does before reasoning about the code.
- Name what is shared across threads and what owns each piece of state.
- Identify the window where an invariant is briefly untrue.
- 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 do you manage error handling in a nested asynchronous flow to prevent application crashes?
How do you manage error handling in a nested asynchronous flow to prevent application crashes?
Approach
- Say what the runtime actually does before reasoning about the code.
- Name what is shared across threads and what owns each piece of state.
- Identify the window where an invariant is briefly untrue.
- 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?
What are the differences between using promises, async/await, and callbacks, and when would you choose one ove
What are the differences between using promises, async/await, and callbacks, and when would you choose one over the other?
Approach
- Say what the runtime actually does before reasoning about the code.
- Name what is shared across threads and what owns each piece of state.
- Identify the window where an invariant is briefly untrue.
- 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 do you optimize query performance in MongoDB for high-frequency time-series data, such as real-time solar
How do you optimize query performance in MongoDB for high-frequency time-series data, such as real-time solar power generation?
Approach
- Name the grain you start from and join outward from it.
- Check whether any join is one-to-many before aggregating, or the sums inflate.
- Say which index the query would use, and what makes it unusable.
- Handle the rows that do not match: that is usually the actual question.
Follow-up
- How does the query change if that join becomes one-to-many?
- What happens to this when the table is ten times larger?
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?
How would you structure a Node.js application to ensure high modularity and ease of testing?
How would you structure a Node.js application to ensure high modularity and ease of testing?
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?
Explain how you would optimize a slow-running Node.js process that is bottlenecked by CPU-intensive tasks.
Explain how you would optimize a slow-running Node.js process that is bottlenecked by CPU-intensive tasks.
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 MongoDB database schema for a solar installation tracking system, ensuring relationships between cust
Design a MongoDB database schema for a solar installation tracking system, ensuring relationships between customers, physical components, and installation teams are optimized.
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?
When designing a MongoDB database, how do you decide between embedding documents and referencing them?
When designing a MongoDB database, how do you decide between embedding documents and referencing them?
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 your approach to handling database migrations in a production environment with zero downtime.
Describe your approach to handling database migrations in a production environment with zero downtime.
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 would you implement transaction-like behavior in MongoDB across multiple collections?
How would you implement transaction-like behavior in MongoDB across multiple collections?
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?
Write a complete Node.js application that exposes RESTful GET, POST, PUT, and DELETE endpoints to perform CRUD
Write a complete Node.js application that exposes RESTful GET, POST, PUT, and DELETE endpoints to perform CRUD operations on a MongoDB database.
Approach
- Say who the caller is and what they do when the call fails halfway.
- Define the identity of a request so a retry cannot double-apply it.
- Separate accepted, pending, failed and confirmed; they are different facts.
- Design the error taxonomy before the success shape; callers branch on it.
Follow-up
- What happens if the caller retries after a timeout?
- How does a client discover it is on an old version of this contract?
How do you ensure your API responses use correct HTTP status codes and return standardized JSON payloads?
How do you ensure your API responses use correct HTTP status codes and return standardized JSON payloads?
Approach
- Say who the caller is and what they do when the call fails halfway.
- Define the identity of a request so a retry cannot double-apply it.
- Separate accepted, pending, failed and confirmed; they are different facts.
- Design the error taxonomy before the success shape; callers branch on it.
Follow-up
- What happens if the caller retries after a timeout?
- How does a client discover it is on an old version of this contract?
Write a pseudo-code implementation of an API endpoint that handles incoming IoT device data, validates the pay
Write a pseudo-code implementation of an API endpoint that handles incoming IoT device data, validates the payload, and writes it to a database without using external helper libraries.
Approach
- Say who the caller is and what they do when the call fails halfway.
- Define the identity of a request so a retry cannot double-apply it.
- Separate accepted, pending, failed and confirmed; they are different facts.
- Design the error taxonomy before the success shape; callers branch on it.
Follow-up
- What happens if the caller retries after a timeout?
- How does a client discover it is on an old version of this contract?
How would you design a secure authentication and authorization mechanism for an API exposed to both mobile cli
How would you design a secure authentication and authorization mechanism for an API exposed to both mobile clients and third-party partners?
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?
What strategies do you use to rate-limit APIs and prevent abuse from external clients?
What strategies do you use to rate-limit APIs and prevent abuse from external clients?
Approach
- Say who the caller is and what they do when the call fails halfway.
- Define the identity of a request so a retry cannot double-apply it.
- Separate accepted, pending, failed and confirmed; they are different facts.
- Design the error taxonomy before the success shape; callers branch on it.
Follow-up
- What happens if the caller retries after a timeout?
- How does a client discover it is on an old version of this contract?
Read latency spikes on a sixty-second sawtooth
The cached listing read path serves about 14k reads/second at an 85% hit rate. p99 sits at 35 ms for 57 seconds, jumps to 900 ms for 3, and repeats. During each spike the primary shows several hundred identical listing queries starting within the same millisecond, all carrying one large tenant's id. Cache entries use a 60-second TTL. Give the mechanism, the ordered checks, the fix, and the correctness hazard your fix must not introduce.
Approach
- Match the period to a configured number before theorising about load. A spike every 60 seconds against a 60-second TTL is an entry expiring, and you confirm it by correlating spike timestamps with the entry's write time rather than with the traffic curve. If the period had matched a cron or a GC interval instead, this is a different investigation.
- Establish the concurrency of the miss. Several hundred identical queries in one millisecond means the miss path has no coalescing: every request that arrives between expiry and repopulation recomputes. The herd size is that key's arrival rate times its recompute time, so at 1.2k reads/second for the hot key and a 250 ms recompute you expect about 300 concurrent misses, which matches what is observed.
- Add single-flight on the miss path so one caller per key recomputes under a short-lived lock while the rest wait for its result. Prefer stale-while-revalidate where the read tolerates it: return the expired value immediately and refresh asynchronously, which removes the latency spike rather than serialising it into a queue of waiters.
- De-synchronise the keys. Write TTLs with jitter, for example 60 seconds plus or minus 10%, so a deploy or a mass invalidation does not align every key on the same second and turn a per-key herd into a fleet-wide one.
Follow-up
- The same sawtooth appears on a key that is invalidated on write rather than expired. Is that the same bug?
- How does your answer change if the recompute takes 4 seconds instead of 250 ms?
Built from the rounds and topics Solarsquare candidates report.
Prepare, practise & reflect
One practical outcome each day. Spend longer where you need it.
0 / 7 done01Map the Solarsquare loop
- Write out the reported sequence: Initial Screening, Technical Discussions, Hands-on Coding.
- For each round, write one sentence on what it is judging, from the description above, and mark the one you are least ready for.
Deliverable: A one-page map of the 3 reported rounds, with the weakest marked.
02Work RESTful APIs
- Spend the session on RESTful APIs, which Solarsquare candidates report being tested on.
- Write one worked example in RESTful APIs and time yourself on it.
Deliverable: One timed worked example in RESTful APIs.
03Work Node.js
- Spend the session on Node.js, which Solarsquare candidates report being tested on.
- Write one worked example in Node.js and time yourself on it.
Deliverable: One timed worked example in Node.js.
04Work API Design
- Spend the session on API Design, which Solarsquare candidates report being tested on.
- Write one worked example in API Design and time yourself on it.
Deliverable: One timed worked example in API Design.
05Answer out loud: Node.js & Backend Architecture
- Answer aloud, timed: Explain the Node.js event loop and how it handles asynchronous operations under heavy I/O loads.
- Answer aloud, timed: How do you manage error handling in a nested asynchronous flow to prevent application crashes?
Deliverable: Spoken answers to 2 reported Node.js & Backend Architecture question(s), under time.
06Answer out loud: Database Schema & Design
- Answer aloud, timed: Design a MongoDB database schema for a solar installation tracking system, ensuring relationships between customers, physical components, and installation teams are optimized.
- Answer aloud, timed: When designing a MongoDB database, how do you decide between embedding documents and referencing them?
Deliverable: Spoken answers to 2 reported Database Schema & Design question(s), under time.
07Answer out loud: RESTful API Design & Live Coding
- Answer aloud, timed: Write a complete Node.js application that exposes RESTful GET, POST, PUT, and DELETE endpoints to perform CRUD operations on a MongoDB database.
- Answer aloud, timed: How do you ensure your API responses use correct HTTP status codes and return standardized JSON payloads?
Deliverable: Spoken answers to 2 reported RESTful API Design & Live Coding 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.
Ship under a deadline and bound the debt you chose
You have four days to ship a tenant-facing listing endpoint. The version you would defend uses keyset pagination over (tenant_id, status, updated_at DESC, resource_id DESC); the version you can finish uses LIMIT/OFFSET with no matching index. Describe a deadline call you actually made of this shape: what you shipped, what you knowingly deferred, how you bounded the damage with a mechanism rather than an intention, and the specific numeric condition that would force the follow-up. Name who you told and where you wrote it down.
Approach
- Name the deferred failure precisely instead of calling it slow. OFFSET n makes the database produce and discard n rows, so cost grows with page depth; without an index matching the sort, every matching row is read and sorted before the limit applies; and rows inserted between two page fetches shift across the boundary so items are skipped or repeated with nothing in the response to signal it.
- Bound the blast radius with something mechanical rather than a promise: cap maximum page depth, cap page size, restrict the endpoint to one internal caller, or keep it behind a flag. State which failure each cap removes and which it leaves standing.
- Attach a number to the trigger and wire it to an alarm: the first tenant crossing N resources, or the endpoint's p99 crossing its share of the 400 ms budget, so the debt announces itself instead of waiting to be remembered.
- Write it where the next engineer looks, which is the code and the ticket, not a chat message: what was deferred, why, the cap, and the trigger.
Follow-up
- At what page depth does the offset version breach your latency budget, given your page size and row counts?
- What breaks first when you switch to keyset pagination later, and what does a client holding an old page token see?
Argue against a design, lose, and commit anyway
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
- 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.
- 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.
- 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.
- 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?
Turn a code review disagreement into a decision
A colleague's change updates a row with UPDATE resource SET version = version + 1 WHERE resource_id = $1 AND version = $2 and treats an affected-row count of zero as a successful no-op. You read that as a silently lost update; they think returning 200 is friendlier to clients than returning a conflict. Describe how you have handled a review disagreement of this shape: what goes in the comment, when you leave the thread, and who decides. Then write the comment you would leave here, in under 80 words.
Approach
- Sort the disagreement before writing anything. A silently discarded write is a correctness claim about data; the choice between 409 and 412 is taste. Only the first justifies blocking a merge, and saying which one you are doing is most of the value of the comment.
- Make the claim reproducible in the comment itself with an interleaving rather than a principle: A reads version 7, B reads version 7, B commits version 8, A's predicate matches zero rows, A is told it succeeded and A's edit is gone.
- Offer the alternative with its cost attached: return 409 carrying the current version and the revision that won, so the client can re-read and re-apply. Note that automatic retry is not the fix, because a retry re-reads the winner's state and reapplies an intent formed against data that no longer exists.
- Apply an escalation rule you can state: two round trips on the thread, then a call, and the service's owner decides rather than the reviewer. A reviewer who cannot be overruled is a bottleneck with extra steps.
Follow-up
- Where would you put the test that fails if someone reintroduces the swallowed zero rowcount?
- The author says clients cannot handle a 409. How do you check whether that is true?
- 01
You have four days to ship a tenant-facing listing endpoint. The version you would defend uses keyset pagination over (tenant_id, status, updated_at DESC, resource_id DESC); the version you can finish uses LIMIT/OFFSET with no matching index. Describe a deadline call you actually made of this shape: what you shipped, what you knowingly deferred, how you bounded the damage with a mechanism rather than an intention, and the specific numeric condition that would force the follow-up. Name who you told and where you wrote it down.
- 02
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.
- 03
A colleague's change updates a row with UPDATE resource SET version = version + 1 WHERE resource_id = $1 AND version = $2 and treats an affected-row count of zero as a successful no-op. You read that as a silently lost update; they think returning 200 is friendlier to clients than returning a conflict. Describe how you have handled a review disagreement of this shape: what goes in the comment, when you leave the thread, and who decides. Then write the comment you would leave here, in under 80 words.
How difficult are the technical interviews at Solarsquare?
The interviews are generally rated as average in difficulty, but they are highly practical. Instead of testing you on complex, theoretical competitive programming, they focus heavily on real-world coding, API design, and database schema creation.
Solarsquare Software Engineer candidate reports ↗Can I use frameworks and libraries during the coding rounds?
While frameworks like Express are standard, some interview rounds may challenge you to write raw, vanilla Node.js code or pseudo-code without using external npm modules. It is highly recommended to brush up on Node.js core modules.
Solarsquare Software Engineer candidate reports ↗What is the typical timeline from the first screen to an offer?
Solarsquare runs an efficient interview process with fewer rounds than many traditional product companies. The entire process can often be completed within two to three weeks, depending on candidate availability.
Solarsquare Software Engineer candidate reports ↗Is there a strong emphasis on system design?
Yes. The second and third rounds frequently involve deep dives into system architecture, database schema design, and how your backend services scale to handle real-world operational challenges.
Solarsquare Software Engineer candidate reports ↗What topics does Solarsquare test in interviews?
Solarsquare interviews most often cover Node.js, MongoDB, CRUD Operations, HTTP Methods (GET/POST/PUT/DELETE), and HTTP Status Codes. The exact emphasis depends on the specific role you apply for.
Solarsquare 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.
- 01Solarsquare 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