Data & AI engineering leader with 16+ years of experience building and scaling enterprise-grade data platforms across industries.
Currently leading a greenfield, open-source–driven enterprise data platform, enabling modern ETL/ELT, analytics, and AI at scale across hybrid environments (Azure, AWS, on-prem).
Driving AI-powered software development transformation, leveraging generative AI to improve engineering productivity, code quality, and delivery velocity.
Deep expertise in data architecture, distributed systems, and large-scale data pipelines, with hands-on experience across modern data stacks and cloud ecosystems.
Passionate about data observability, lineage, and governance, delivering transparent and reliable data systems using open-source technologies.
Experienced in leading globally distributed, cross-functional teams, aligning engineering execution with business outcomes.
Frequent advocate for practical AI adoption in engineering, including responsible AI, cost optimization (LLM token efficiency), and developer tooling (e.g., AI-assisted coding).
Speaker interests include modern data engineering, AI in SDLC, platform engineering, and building scalable, future-ready data ecosystems.