As a Software Engineer at Next insurance, you play a foundational role in building and scaling the digital insurance platforms that modernize coverage for small businesses. Your daily work directly impacts how self-employed professionals and small business owners secure fast, transparent, and customized insurance policies online. By combining robust backend engineering, clean architecture, and modern web technologies, you help eliminate the traditional friction of the insurance industry. This role sits at the intersection of complex financial logic, high-volume user traffic, and real-time data processing. You will contribute to core product features, microservices architecture, and automated workflows that power quoting, binding, and policy management. The engineering culture values clean code, pragmatic problem-solving, and close collaboration with product and design teams to ship user-facing value rapidly. Expect a fast-paced environment where technical excellence meets direct business ownership. Whether you are optimizing data pipelines, designing scalable services, or refining backend algorithms, your contributions will directly shape the technological backbone of a growing insurtech leader. Success in this role requires both sharp technical execution and a collaborative mindset focused on delivering seamless customer experiences.
Recruiter Screening Call
reportedInitial call to discuss your background, interest in the company, and basic qualifications.
What to demonstrate
- Initial call to discuss your background, interest in the company, and basic qualifications
- Depth in Programming (General Problem Solving)
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 Evaluations
reportedIncludes coding assessments, technical interviews with team leaders or architects, and system design discussions.
What to demonstrate
- Includes coding assessments, technical interviews with team leaders or architects, and system design discussions
- Depth in Programming (General Problem Solving)
How to prepare
- Answer aloud and timed: Find the maximum perfect subtree in a binary tree.
- Answer aloud and timed: Write a function to find the root of a number, accounting for edge cases such as numbers less than one.
Live Coding
reportedEvaluation of coding abilities and core language knowledge through live coding over Zoom or timed technical assignments.
What to demonstrate
- Evaluation of coding abilities and core language knowledge through live coding over Zoom or timed technical assignments
- Depth in Programming (General Problem Solving)
How to prepare
- Answer aloud and timed: Solve the Two Sum problem efficiently using appropriate data structures.
- Answer aloud and timed: Explain the difference between checked and unchecked exceptions in Java.
Collaborative Problem-Solving
reportedInteractive technical discussions emphasizing collaborative problem-solving and communication of complex concepts.
What to demonstrate
- Interactive technical discussions emphasizing collaborative problem-solving and communication of complex concepts
- Depth in Programming (General Problem Solving)
How to prepare
- Answer aloud and timed: Discuss how constructors work in object-oriented programming and how initialization order matters.
- Answer aloud and timed: Walk through core JVM concepts and memory management principles.
Final Architectural Discussions
reportedConcludes the interview process with discussions focused on architectural concepts.
What to demonstrate
- Concludes the interview process with discussions focused on architectural concepts
- Depth in Programming (General Problem Solving)
How to prepare
- Answer aloud and timed: Explain object-oriented design principles and how you apply them in modular codebases.
- Answer aloud and timed: Discuss how you structure classes and interfaces to maintain high cohesion and low coupling.
PracHub editorial advice for the preparation topics above.
Master the fundamentals
Do not neglect core language trivia and object-oriented concepts; interviewers frequently pair coding questions with deep-dive questions on exceptions, constructors, and memory management.
Communicate proactively
Treat live coding interviews as a collaborative pair-programming session. Never sit in silence while debugging; explain what you are testing and why.
Structure your system design answers
When faced with open-ended design prompts like planning an elevator system, start by defining requirements, establishing scale, and outlining core components before diving into granular details.
Prepare real project stories
Be ready to discuss past technical challenges you faced, how you diagnosed the root cause, and what you learned from the resolution during behavioral and architectural chats.
Choose a category, try a prompt, then open its approach, worked solution or follow-up when you need it.
Find the second maximum element in an array.
Find the second maximum element in an array.
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?
Solve the classic “Number of Islands” matrix traversal challenge.
Solve the classic “Number of Islands” matrix traversal challenge.
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?
Find the maximum perfect subtree in a binary tree.
Find the maximum perfect subtree in a binary tree.
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?
Write a function to find the root of a number, accounting for edge cases such as numbers less than one.
Write a function to find the root of a number, accounting for edge cases such as numbers less than one.
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?
Solve the Two Sum problem efficiently using appropriate data structures.
Solve the Two Sum problem efficiently using appropriate data structures.
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 difference between checked and unchecked exceptions in Java.
Explain the difference between checked and unchecked exceptions in Java.
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?
Discuss how constructors work in object-oriented programming and how initialization order matters.
Discuss how constructors work in object-oriented programming and how initialization order matters.
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?
Walk through core JVM concepts and memory management principles.
Walk through core JVM concepts and memory management principles.
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?
Explain object-oriented design principles and how you apply them in modular codebases.
Explain object-oriented design principles and how you apply them in modular codebases.
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?
Discuss how you structure classes and interfaces to maintain high cohesion and low coupling.
Discuss how you structure classes and interfaces to maintain high cohesion and low coupling.
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?
Hold a per-tenant active cap against concurrent creates
A tenant on the standard plan may hold at most 50 resources with status='active'. The create handler runs SELECT count(*) FROM resource WHERE tenant_id = $1 AND status = 'active', compares to 50, then inserts. Two creates arrive 3 ms apart on different instances and the tenant lands at 51. Name the anomaly, say whether PostgreSQL 16 READ COMMITTED or REPEATABLE READ prevents it and why, then give an implementation that holds the cap at READ COMMITTED with the exact statements. Finally, say what changes when the cap is 'at most one running export per tenant' on job_run.
Approach
- Name it: write skew. The two transactions read an overlapping set and write disjoint rows, so there is no row-level conflict for the engine to detect and each commit is individually legal.
- Rule out the levels precisely. READ COMMITTED takes a fresh snapshot per statement and takes no lock on the counted rows, so both see 49. PostgreSQL's REPEATABLE READ is snapshot isolation: it removes non-repeatable reads and phantoms within the snapshot but still admits write skew, because the anomaly is not a re-read of a changed row, it is a read of a set that a concurrent transaction invalidates. Only SERIALIZABLE closes it, by tracking the read dependency and aborting one transaction with SQLSTATE 40001 — a guarantee that exists only if the application re-runs the whole transaction from the read.
- Convert the set predicate into a single-row conflict: keep tenant.active_resource_count and run UPDATE tenant SET active_resource_count = active_resource_count + 1 WHERE tenant_id = $1 AND active_resource_count < 50 in the same transaction as the INSERT. Zero affected rows is the cap, returned as 409. The row lock serialises the decision at any isolation level, and contention is bounded to one tenant's row — which is also the fair-scheduling unit, unlike a global counter that would convoy every tenant behind one row.
- State the cost you just took on: a counter is a second source of truth that can drift, so every path that changes status must adjust it inside the same transaction, and a periodic reconciliation has to exist, with resource_revision as the authority for what the count should have been.
Follow-up
- A resource moves from archived back to active. Which statements change, and what breaks if the counter update and the status change land in different transactions?
- The cap becomes plan-dependent and a plan can change mid-month. Where does the number 50 live, and who reads it?
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?
Plan and design a fully functional elevator system architecture under specific constraints.
Plan and design a fully functional elevator system architecture under specific constraints.
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?
Discuss high-level technological considerations with engineering leadership and chief architects.
Discuss high-level technological considerations with engineering leadership and chief architects.
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?
Describe how you approach scaling microservices to handle fluctuating traffic loads.
Describe how you approach scaling microservices to handle fluctuating traffic loads.
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 manage state and data consistency across distributed insurance workflows.
Explain how you manage state and data consistency across distributed insurance workflows.
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?
Outline your strategy for logging, monitoring, and debugging complex production services.
Outline your strategy for logging, monitoring, and debugging complex production services.
Approach
- Establish what changed and when, before forming any theory.
- Pick a bisection that eliminates candidates whichever way it turns out.
- Check the instrumentation before believing the symptom.
- Separate the trigger from the cause; the deploy is rarely the bug.
Follow-up
- What would you look at first, and what would it rule out?
- How would you tell a cause from a coincidence here?
Built from the rounds and topics Next insurance candidates report.
Prepare, practise & reflect
One practical outcome each day. Spend longer where you need it.
0 / 7 done01Map the Next insurance loop
- Write out the reported sequence: Recruiter Screening Call, Technical Evaluations, Live Coding, Collaborative Problem-Solving, Final Architectural Discussions.
- For each round, write one sentence on what it is judging, from the description above, and mark the one you are least ready for.
Deliverable: A one-page map of the 5 reported rounds, with the weakest marked.
02Work Programming (General Problem Solving)
- Spend the session on Programming (General Problem Solving), which Next insurance candidates report being tested on.
- Write one worked example in Programming (General Problem Solving) and time yourself on it.
Deliverable: One timed worked example in Programming (General Problem Solving).
03Work System Design
- Spend the session on System Design, which Next insurance 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.
04Work Java Programming
- Spend the session on Java Programming, which Next insurance candidates report being tested on.
- Write one worked example in Java Programming and time yourself on it.
Deliverable: One timed worked example in Java Programming.
05Answer out loud: Technical / Coding / Algorithms
- Answer aloud, timed: Find the second maximum element in an array.
- Answer aloud, timed: Solve the classic “Number of Islands” matrix traversal challenge.
Deliverable: Spoken answers to 2 reported Technical / Coding / Algorithms question(s), under time.
06Answer out loud: Object-Oriented Programming & Core Language Concepts
- Answer aloud, timed: Explain the difference between checked and unchecked exceptions in Java.
- Answer aloud, timed: Discuss how constructors work in object-oriented programming and how initialization order matters.
Deliverable: Spoken answers to 2 reported Object-Oriented Programming & Core Language Concepts question(s), under time.
07Answer out loud: System Design & Architecture
- Answer aloud, timed: Plan and design a fully functional elevator system architecture under specific constraints.
- Answer aloud, timed: Discuss high-level technological considerations with engineering leadership and chief architects.
Deliverable: Spoken answers to 2 reported System Design & Architecture 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.
Tell me about yourself and what technical challenges you are currently working on.
Tell me about yourself and what technical challenges you are currently working on.
Approach
- Pick a story where you made the decision, not one where you watched it.
- State the situation in two sentences and spend the rest on the reasoning.
- Give the blast radius: what could have broken, and what you measured.
- Name the disagreement and how you resolved it with evidence.
Follow-up
- What would you do differently if you ran that again?
- How did you know your change caused the improvement?
Describe a complex technical problem you faced in a previous role and walk through how you fixed it.
Describe a complex technical problem you faced in a previous role and walk through how you fixed 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?
Discuss a disagreement you had with a teammate regarding an architectural or coding decision and how you resol
Discuss a disagreement you had with a teammate regarding an architectural or coding decision and how you resolved it.
Approach
- Pick a story where you made the decision, not one where you watched it.
- State the situation in two sentences and spend the rest on the reasoning.
- Give the blast radius: what could have broken, and what you measured.
- Name the disagreement and how you resolved it with evidence.
Follow-up
- What would you do differently if you ran that again?
- How did you know your change caused the improvement?
How do you prioritize tasks when facing competing deadlines from product and engineering stakeholders?
How do you prioritize tasks when facing competing deadlines from product and engineering stakeholders?
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 building software specifically within the insurtech domain?
Why are you interested in building software specifically within the insurtech domain?
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
Tell me about yourself and what technical challenges you are currently working on.
- 02
Describe a complex technical problem you faced in a previous role and walk through how you fixed it.
- 03
Discuss a disagreement you had with a teammate regarding an architectural or coding decision and how you resolved it.
- 04
How do you prioritize tasks when facing competing deadlines from product and engineering stakeholders?
How difficult is the technical interview process at Next insurance?
The technical evaluation is rigorous but straightforward, focusing heavily on standard data structures, algorithms, and core language mechanics. While the problems are manageable if you practice consistently, interviewers expect clean code and clear verbal reasoning.
Next insurance Software Engineer candidate reports ↗How much time should I spend preparing for the interviews?
Most candidates benefit from 3 to 4 weeks of dedicated preparation. Focus your time on solving medium-level coding problems, reviewing object-oriented programming principles, and practicing system design fundamentals.
Next insurance Software Engineer candidate reports ↗What is the best way to stand out during the coding rounds?
Always clarify the problem constraints and edge cases before writing code. Talk through your thought process out loud, write clean and modular code, and proactively test your solution with sample inputs before submitting.
Next insurance Software Engineer candidate reports ↗How are remote or hybrid work preferences handled?
Work arrangements depend on the specific office location and team hub, such as Kfar Saba or Tel Aviv engineering centers. Recruiters will clarify specific hybrid expectations and office presence guidelines during your initial HR screen.
Next insurance Software Engineer candidate reports ↗What happens after I submit a take-home assignment or complete a technical round?
The engineering team typically maintains a responsive feedback loop, though timelines can vary. If you move forward, your recruiter will coordinate subsequent technical discussions and architectural interviews promptly.
Next insurance Software Engineer candidate reports ↗What topics does Next insurance test in interviews?
Next insurance interviews most often cover Stakeholder Communication, SQL, Insurance Domain Knowledge, Behavioral Interviewing, and Java. The exact emphasis depends on the specific role you apply for.
Next insurance 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.
- 01Next insurance 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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