Nitin Duseja
Résumé

Case 03 · mint channel

Paytm DLT & SMS Engine

Distributed ledger technology & mission-critical transaction messaging at scale

Year
2022
Role
Senior Software Engineer
Team
Distributed Systems Pod · Paytm
Duration
Ongoing

The problem

What was being asked

Context

Telecom compliance and financial integrity mandated a tamper-proof Distributed Ledger Technology (DLT) framework to verify, register, and audit financial transaction messaging at staggering scale (20M+ SMS/day).

The solution

What was built

Slip 1

Spearheaded development of DLT integration leveraging Hyperledger Blockchain and decentralized ledgers for auditability

Slip 2

Refactored backend scheduler and worker modules, enhancing execution performance by 50% and slashing latency under peak loads

Slip 3

Built distributed worker pools with Redis and Node.js to ingest and process high-volume telecommunication event streams

The architecture

How it holds together

Hyperledger Ledger Layer

Decentralized consensus nodes recording tamper-proof message templates, entity registrations, and verification proofs.

High-Throughput Scheduler Pipeline

Optimized Node.js and Laravel workers consuming high-priority transactional queues with idempotent execution and sub-50ms dispatch.

Key Metrics & Impact

Demonstrated Results

Challenges

The parts that tried to break it

Extreme throughput spikes

Financial and OTP traffic surges during flash sales required dynamic worker auto-scaling and zero-downtime queue draining.

Immutable compliance verification

Strict telecom regulations required deterministic signature verification across millions of records without database lock contention.

Decisions

Calls somebody owns

Hyperledger for enterprise compliance

Offered enterprise-grade permissioned ledger control, compliance guarantees, and predictable consensus times.

In-memory caching of active templates

Cached approved message hashes in Redis to minimize cryptographic lookups on hot paths.

Learning carried forward

At enterprise scale, a 50% optimization in scheduler throughput translates directly to infrastructure savings, lower latencies, and bulletproof user trust during critical financial operations.