Aurobindo Mondal

Software Engineer

Bengaluru, Karnataka, India11 yrs 6 mos experience

Most Likely To SwitchHighly Stable

Key Highlights

Expert in architecting complex data systems.
Proven track record in Fintech and Big Data projects.
Strong foundation in Computer Science from IIT Bombay.

Stackforce AI infers this person is a Backend-focused engineer with expertise in Fintech and Big Data solutions.

Contact

aurobindoc1991@gmail.com LinkedIn

Skills

Core Skills

JavaApache SparkTemporalDropwizard

Other Skills

AlgorithmsAndroid DevelopmentBack-End Web DevelopmentBig DataCC++Computer NetworkingData StructuresDistributed SystemsHBaseKernelLinuxProgrammingRedisSQL

About

Experienced Member Of Technical Staff with a demonstrated history of working in the computer networking industry. Skilled in Python, Computer Networking, Java, Linux Kernel, and C. Strong engineering professional with a Master's Degree focused in Computer Science from Indian Institute of Technology, Bombay.

Experience

Flipkart

4 roles

SDE 4

Oct 2025 – Present · 5 mos

SDE 3

Promoted

Oct 2022 – Dec 2025 · 3 yrs 2 mos

1. Amsterdam (Onboarding Platform)
Architected & Developed "Amsterdam," a unified onboarding platform for Co-branded Credit Cards and EMI products across the entire Flipkart group ecosystem (Flipkart, Myntra, Cleartrip).
Implemented durable, stateful workflows using Temporal, ensuring reliability across complex, long-running cross-entity processes.
Tech Stack: Temporal.io, Spring Boot, Java, SQL.
2. Dexter Decision Engine (FinTech/Risk)
Architected and built "Dexter," a real-time risk analysis and decisioning engine that manages credit lifecycles for millions of users.
Engineered a custom rule evaluator using binary tree traversal algorithms to parse and execute dynamic risk policies with low latency.
Tech Stack: Java, Dropwizard, HBase, Custom DSL/Expression Evaluators.
3. Speedforce (Data Pipeline)
Designed "Speedforce," a high-throughput data bridge to synchronize offline Google Cloud Storage (GCS) data with the online serving layer (Yak) in near real-time.
Optimized data ingestion pipelines using Apache Spark and Redis, significantly reducing data availability latency for critical business operations.
Tech Stack: Apache Spark, Java, HBase, Redis.