Navi Technologies, founded by Sachin Bansal, runs a demanding SDE loop that skews toward strong DSA and scalable system design across lending, UPI, insurance, and mutual funds.
Expect at least one hard DSA round (trees, graphs, dynamic programming, greedy) and a system design round where you design at scale: think a loan-disbursal pipeline, a UPI transaction service, or a high-throughput notification system. Navi is known for a high engineering bar and fast-moving teams, so interviewers push on capacity estimation, consistency versus availability trade-offs, and how your design fails gracefully under load. Depth of reasoning beats memorised templates here.
About Navi Technologies
Navi Technologies is a Bengaluru fintech founded by Sachin Bansal (ex-Flipkart) offering health insurance, personal loans, home loans, UPI payments, and mutual funds under one app.
Resume screen: strong backend and DSA signal; referrals help significantly
Online assessment: 2 to 3 DSA problems, roughly 90 minutes
Problem-solving coding rounds: medium to hard DSA with complexity follow-ups
System design round: scalable architecture and trade-offs (SDE-2+ primarily)
Hiring manager and culture round: ownership, speed, and values fit
Online Assessment (90 min)
2 to 3 medium-hard DSA problems. Most candidates are filtered here.
Problem Solving x1 to x2 (45 to 60 min each)
Harder DSA on trees, graphs, and DP with follow-up complexity and edge-case questions.
System Design (60 min, SDE-2+)
Design a lending, UPI, or notification system at scale. Begin with capacity estimates before jumping to a solution.
Hiring Manager and Culture (45 min)
Ownership, comfort with fast iteration, and alignment with Navi's high-bar engineering culture.
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 Navi Technologies recruitment process has 5 stages: Resume screen: strong backend and DSA signal; referrals help significantly → Online assessment: 2 to 3 DSA problems, roughly 90 minutes → Problem-solving coding rounds: medium to hard DSA with complexity follow-ups → System design round: scalable architecture and trade-offs (SDE-2+ primarily) → Hiring manager and culture round: ownership, speed, and values fit.
Navi Technologies typically conducts 4 interview rounds: Online Assessment (90 min): 2 to 3 medium-hard DSA problems. Most candidates are filtered here.; Problem Solving x1 to x2 (45 to 60 min each): Harder DSA on trees, graphs, and DP with follow-up complexity and edge-case questions.; System Design (60 min, SDE-2+): Design a lending, UPI, or notification system at scale. Begin with capacity estimates before jumping to a solution.; Hiring Manager and Culture (45 min): Ownership, comfort with fast iteration, and alignment with Navi's high-bar engineering culture..
HireStepX recommends the Scale-and-fail design framework for this type of interview: Estimate QPS and storage, choose data model, define consistency trade-offs, then failure and degradation paths.
To answer this question well, HireStepX recommends the Scale-and-fail design approach: Estimate QPS and storage, choose data model, define consistency trade-offs, then failure and degradation paths. Ground your answer in a specific real example from your own experience.
To answer this question well, HireStepX recommends the Scale-and-fail design approach: Estimate QPS and storage, choose data model, define consistency trade-offs, then failure and degradation paths. Ground your answer in a specific real example from your own experience.
To answer this question well, HireStepX recommends the Scale-and-fail design approach: Estimate QPS and storage, choose data model, define consistency trade-offs, then failure and degradation paths. Ground your answer in a specific real example from your own experience.
To answer this question well, HireStepX recommends the Scale-and-fail design approach: Estimate QPS and storage, choose data model, define consistency trade-offs, then failure and degradation paths. Ground your answer in a specific real example from your own experience.
To answer this question well, HireStepX recommends the Scale-and-fail design approach: Estimate QPS and storage, choose data model, define consistency trade-offs, then failure and degradation paths. Ground your answer in a specific real example from your own experience.