With 18 years of experience turning complex data ecosystems into real business value, I work at the intersection of Data Architecture, AI/ML Engineering, and Cloud Platforms — designing solutions that don’t just look good on paper, but operate reliably at scale.

My background spans enterprise data platforms, real-time streaming, cloud engineering, and full‑stack MLOps. I’ve architected and delivered large-scale systems using Palantir Foundry, Kafka, Databricks, Azure, AWS, Snowflake, and modern containerized environments. My work includes ontology design, streaming architectures, Lakehouse implementations, data contracts, and governance frameworks that keep organizations compliant and future‑ready.

On the machine learning side, I build end‑to‑end pipelines — from feature engineering and model training to deployment, monitoring, and GenAI/RAG applications. I’ve delivered real-world AI solutions including custom chatbots, semantic search systems, and ML governance workflows using tools like MLflow, Azure ML, and Foundry AIP.

Governance is a core part of my engineering philosophy. I embed controls, lineage, cataloging, and compliance into every architecture using platforms such as Unity Catalog, Collibra, and Purview.

I hold certifications including AWS Solutions Architect, AWS Data Analytics, PMP, and CSM, and I’m passionate about helping data professionals grow into senior architectural and AI-driven roles.