Vishal Kamlapure
Senior GenAI Data Engineer | Real-time Data & Streaming Platforms | Apache Flink (Contributor) • Kafka • AWS • Spark | Building GenAI-ready Data Infrastructure
- Role
- Senior Genai Data Engineer at IDFC FIRST Bank
- Location
- Mumbai, MH, IN
- LinkedIn followers
- 500 followers
About Vishal Kamlapure
I am a Senior Data & Streaming Engineer with experience architecting and operating large-scale, production-grade data platforms across banking, capital markets, ed-tech, and telecom domains.My core expertise lies in owning and designing low-latency batch and real-time data systems using Apache Flink, Kafka, Spark, and cloud-native architectures. I focus strongly on system correctness, scalability, and operational stability, particularly in data-critical and regulated environments.Recently, I have been building and integrating Generative AI data platforms, including:* Retrieval-Augmented Generation (RAG) pipelines * Vector databases and embedding workflows * Real-time and CDC-based data ingestion for AI systems * Cost, latency, and reliability considerations for GenAI in productionI work at the intersection of distributed systems, data engineering, and applied GenAI, where strong data foundations are essential to make AI systems accurate, explainable, and safe.Alongside hands-on engineering, I lead and mentor engineers, collaborate with product and platform teams, and drive technical decisions from architecture design through production rollout.I am particularly interested in GenAI data platforms, streaming systems, and AI-enabled infrastructure roles, where engineering rigor and long-term system ownership matter more than demos or prototypes.
Experience
Senior Genai Data Engineer
Mar 2025 — Present · Mumbai, IN
Architected and deployed an Apache Flink-based streaming pipeline on AWS EMR, processing millions of daily transactions (UPI, savings, credit card, and app-based).• Reduced end-to-end pipeline latency from ~30 minutes (batch) to < 7 seconds,(including ML inference on AWS EKS) by optimizing Flink pre- and post-processing to ~300ms each, enabling near real-time transaction categorization.• Eliminated microservice layer by enabling direct asynchronous ML API calls from Flink, reducing system complexity and improving throughput by 40%.
Education
University of Mumbai
Bachelor of Engineering - BE, Computer Engineering
2016 — 2020
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