Teams at Vanguard

Designs and leads scalable AWS and Databricks data pipelines, data models, quality frameworks, monitoring, testing, and production deployments. Investigates ambiguous data and business problems independently, translating requirements into secure, reliable technical solutions. Mentors engineers, establishes architecture and coding standards, and partners with architecture, analytics, product, and business teams. Supports AI readiness, data unification, metadata strategy, and enterprise integration initiatives.

Leads the architecture and delivery of enterprise data engineering solutions using Databricks, AWS, and Lakehouse technologies. Builds scalable batch and streaming pipelines, reusable metadata-driven frameworks, governed data products, and AI-ready foundations. Leads platform modernization, data quality, observability, CI/CD, infrastructure automation, and Generative AI enablement. Mentors engineers, advises stakeholders, and drives architecture standards, governance, and technical initiatives.

Leads AI research teams and guides advanced research initiatives from experimentation through production adoption. Evaluates emerging AI methods, oversees rigorous benchmarking and validation, builds academic and internal partnerships, and collaborates with engineering, product, and business teams. The role balances exploratory research with enterprise delivery while advancing responsible, secure, reliable, and scalable AI capabilities. It also influences AI strategy, technical investment decisions, and organizational standards for research excellence.