Vineel Arekapudi
Engineering Data Platforms from Storage to API, Senior Data Engineer Consultant at Wells Fargo
I work at the intersection of large-scale data engineering, cloud platforms, and applied AI. I currently build and lead modern data platforms at a major U.S. bank, where I design Lakehouse and streaming architectures that operate at multi-billion-record scale across cloud environments. My background spans the full evolution of enterprise data systems, from mainframe and Teradata warehouses to cloud-native lakehouses built on Spark, Iceberg, Kafka, and Kubernetes. Over the past decade, my work has focused on building production-grade data platforms: high-throughput ingestion pipelines, real-time analytics systems, and ML-ready data infrastructure used by data scientists, analysts, and AI teams. In addition to data engineering, I have deep experience in full-stack platform development using Java, Spring Boot, REST APIs, and modern front-end frameworks. This allows me to design data systems not just as pipelines, but as products — complete with APIs, services, governance layers, and developer tooling. My current interests include open table formats (Apache Iceberg), lakehouse architecture, metadata-driven governance, and building scalable AI-ready data platforms. I enjoy sharing practical lessons from real production systems — what works, what breaks, and how to design data infrastructure that lasts.