Lead Data Engineer & Enterprise Data Architect · Founder, DE Copilot
I have spent over 15 years designing and delivering large-scale data platforms across insurance, retail, and financial services. My work focuses on the intersection of AI, metadata governance, and practical engineering delivery not theoretical frameworks, but patterns that teams can implement and trust.
I built DE Copilot to solve a problem I kept encountering: teams spending significant time translating the same metadata into different formats, repeatedly, without a governed workflow. The platform turns business requirements, STTMs, and legacy ETL metadata into validated, reviewable engineering deliverables.
I enjoy sharing practical, real-world lessons that engineering teams can immediately apply not product demonstrations, but architecture patterns, governance models, and implementation strategies grounded in enterprise experience.
Each session is grounded in real enterprise delivery experience. Topics can be tailored for conference keynotes, technical deep-dives, meetups, webinars, podcasts, or corporate training sessions.
Practical ways AI is transforming enterprise data engineering from metadata extraction and artifact generation to governed delivery workflows and human-in-the-loop review.
Building reusable, scalable, and governed data platforms by normalizing business requirements and source-to-target mappings into a Canonical Metadata Model.
Lessons learned from designing and delivering modern cloud data platforms data modeling, semantic layers, Cortex Analyst, data quality, and observability.
Architecture, governance, human review, and production readiness for AI-assisted engineering tools what it takes to move from prototype to trusted enterprise delivery.
Designing trusted data pipelines for enterprise reporting validation controls, reconciliation, DQ rule generation, and release gates that keep engineers in control.
Using metadata to automate SQL generation, documentation, testing, lineage, and deployment while preserving traceability and human approval at every step.
Technical topics submitted to and accepted at conferences, meetups, and community events.
Active call-for-proposals submissions for 2026 conferences.
PyBay 2026
Conference · San Francisco, CA
DevFest KC
Conference · Kansas City, MO
AI Dev World
Conference · TBD
Open to speaking engagements across a wide range of formats and venues.
Enterprise conferences
Data, AI, and technology conferences
Meetups
Local and virtual engineering meetups
Hackathons
Technical sessions and workshops
Internal engineering summits
Corporate engineering all-hands and summits
AI events
AI and machine learning focused events
Data Engineering conferences
Data platform and pipeline conferences
Python conferences
PyCon, PyBay, and regional Python events
Podcasts
Technical podcast interviews and panels
Guest lectures
University and bootcamp guest sessions
Webinars
Online technical sessions and workshops
Sessions are designed for practitioners and leaders who work with data platforms, AI systems, and engineering delivery at scale.
Technical judging for AI hackathons evaluating architecture, governance, production readiness, and real-world applicability of AI-powered solutions.
Publishing practical articles on metadata-driven engineering, ETL modernization, Snowflake architecture, and AI-assisted data delivery at dataengineeringcopilot.com.
Contributing to open-source projects and AI and data engineering research focused on governed, metadata-first delivery workflows.
Founder of DE Copilot a metadata intelligence platform turning business requirements, STTMs, and legacy ETL assets into validated, reviewable engineering deliverables.
Accepting invitations for meetups, conferences, webinars, podcasts, and technical community events. Sessions can be tailored to your audience and format.
Future talks will appear here
Speaker photos, slides, recordings, and event details will be added as presentations are confirmed and completed.
Sessions built for engineers and technical leaders who want patterns they can apply immediately — not slides they'll forget by Monday.
15+ years delivering enterprise data platforms across insurance, retail, financial services, and e-commerce. Every pattern is grounded in real delivery experience.
Creator of an AI-powered metadata intelligence platform. Sessions include real architecture decisions, tradeoffs, and lessons from building a production platform.
Technical judge for MLH, DEV, LabLab.ai, and SANS Institute competitions. Brings a practitioner's lens to evaluating AI architecture, quality, and real-world applicability.
12+ published articles on metadata engineering, Snowflake, enterprise AI, and data quality. Writing that reflects how enterprise engineers actually think and work.
Sessions include live or recorded demonstrations of real platform capabilities — not mockups. Attendees see actual metadata-to-artifact workflows in action.
Every session ends with concrete takeaways: design patterns, governance models, and workflow approaches that translate directly into engineering practice.
Everything you need to promote and plan a session. Additional materials available on request.
Short and long-form bios available for conference programs, event pages, and promotional materials.
Request via emailFull professional background, career history, and community contributions on LinkedIn.
View on LinkedIn10+ published articles on AI, metadata-driven engineering, Snowflake, and enterprise data architecture.
Browse the blogFull session abstracts, learning objectives, and audience takeaways for each speaking topic.
Request via emailFull founder profile, career timeline, expertise areas, and community leadership background.
View about pageFor press, podcast, or media requests, reach out directly via email or LinkedIn.
Get in touchI welcome invitations for conferences, meetups, webinars, podcasts, guest lectures, and corporate technology sessions. Let's discuss how I can contribute to your event.