PolicyBazaar (PB Fintech) runs a practical SDE loop weighted toward DSA fundamentals and hands-on backend or full-stack skills over abstract theory.
Expect a coding round on medium DSA (arrays, strings, hashmaps, linked lists, trees) plus a technical round on your primary stack, commonly Java or Node with SQL and REST API design. Because the platform handles insurance quotes, lead funnels, and high traffic during campaigns, interviewers ask about database indexing, query optimisation, caching, and how you keep APIs fast under spikes. Clear fundamentals and real project depth land better than name-dropping frameworks.
About PolicyBazaar
PolicyBazaar (PB Fintech) is India's largest insurance and lending marketplace, listed on NSE (POLICYBZR). It aggregates health, motor, life, and investment products from 50+ insurers.
Resume screen: relevant backend or full-stack experience; referrals help
Online or written coding round: medium DSA, roughly 60 to 90 minutes
Technical round on stack: Java or Node, SQL, REST API and schema design
Second technical round: problem solving, indexing, caching, and system reasoning
Hiring manager and HR round: fit, expectations, and compensation
Coding Round (60 to 90 min)
Medium DSA on arrays, strings, hashmaps, linked lists, and trees. The primary early filter.
Technical Round 1 (45 to 60 min)
Deep dive on your stack, REST API design, SQL queries, and past project decisions.
Technical Round 2 (45 to 60 min)
Problem solving plus database indexing, query optimisation, and caching for high-traffic scenarios.
Hiring Manager and HR (30 to 45 min)
Ownership, communication, expectations, and compensation discussion.
Sourced from 2+ candidate post-mortems. Hit Practice to answer any one with AI voice feedback.
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Sign up free: unlock all questionsThe typical PolicyBazaar recruitment process has 5 stages: Resume screen: relevant backend or full-stack experience; referrals help → Online or written coding round: medium DSA, roughly 60 to 90 minutes → Technical round on stack: Java or Node, SQL, REST API and schema design → Second technical round: problem solving, indexing, caching, and system reasoning → Hiring manager and HR round: fit, expectations, and compensation.
PolicyBazaar typically conducts 4 interview rounds: Coding Round (60 to 90 min): Medium DSA on arrays, strings, hashmaps, linked lists, and trees. The primary early filter.; Technical Round 1 (45 to 60 min): Deep dive on your stack, REST API design, SQL queries, and past project decisions.; Technical Round 2 (45 to 60 min): Problem solving plus database indexing, query optimisation, and caching for high-traffic scenarios.; Hiring Manager and HR (30 to 45 min): Ownership, communication, expectations, and compensation discussion..
HireStepX recommends the Fundamentals-first backend framework for this type of interview: Solid DSA, then clean API and schema design, then indexing and caching for traffic spikes.
To answer this question well, HireStepX recommends the Fundamentals-first backend approach: Solid DSA, then clean API and schema design, then indexing and caching for traffic spikes. Ground your answer in a specific real example from your own experience.
To answer this question well, HireStepX recommends the Fundamentals-first backend approach: Solid DSA, then clean API and schema design, then indexing and caching for traffic spikes. Ground your answer in a specific real example from your own experience.
To answer this question well, HireStepX recommends the Fundamentals-first backend approach: Solid DSA, then clean API and schema design, then indexing and caching for traffic spikes. Ground your answer in a specific real example from your own experience.
To answer this question well, HireStepX recommends the Fundamentals-first backend approach: Solid DSA, then clean API and schema design, then indexing and caching for traffic spikes. Ground your answer in a specific real example from your own experience.
To answer this question well, HireStepX recommends the Fundamentals-first backend approach: Solid DSA, then clean API and schema design, then indexing and caching for traffic spikes. Ground your answer in a specific real example from your own experience.