I am a Big Data and AI/ML Engineer with 14+ years of IT experience, specializing in the design and implementation of scalable, robust, real-time and near real-time data platforms across Hadoop-based and cloud-native architectures. I have extensive experience working with large-scale, high-throughput data systems, translating complex business requirements into high-performance, reliable, and maintainable solutions.

Data Engineering & Analytics:

I have designed and delivered end-to-end data engineering frameworks using technologies such as Spark, Kafka, Presto, Hive, HBase, Sqoop, Airflow, and Oozie, enabling efficient ingestion, transformation, analytics, and exploration of high-volume, high-velocity data.
I bring a strong analytical mindset to data exploration, analytics, and data governance, ensuring data quality, consistency, and usability for downstream consumers, including BI platforms, machine learning pipelines, and real-time decision systems.

System Design & Architecture:

I specialize in robust system design, owning the full lifecycle of modern data and AI platforms. My experience spans designing responsive front-end integrations, building scalable backend microservices, and orchestrating high-availability deployments on Kubernetes. I have hands-on expertise in configuring complex networking and distributed system components to ensure seamless, reliable data flow across the entire stack.

Artificial Intelligence & Advanced AI Systems:

Over time, my role has evolved from core data engineering into AI-driven system and platform design. I have built strong expertise in Machine Learning, Deep Learning, and Reinforcement Learning.
I have worked on multiple use case like
- Image classification and segmentation using CNN-based models (YOLO) and Vision Transformers (ViT)
- Traditional ML solutions
- Generative AI and Agentic AI architectures, with a focus on integrating intelligent reasoning systems with scalable data platforms to build autonomous, decision-driven, and production-grade AI solutions