Years across data and systems
Built governed data platforms, analytics capabilities, semantic architectures, and business systems across SaaS organizations.
Data & analytics leadership · Semantic layers · AI-ready enterprise data
Building the trusted data foundations behind enterprise analytics and AI.
I lead data and analytics organizations that build governed data platforms, semantic layers, and enterprise metrics consumed across BI systems, AI agents, conversational analytics, and business applications.
Executive profile
Leadership for governed analytics and AI-driven data consumption.
Data and analytics leader specializing in the architecture, governance, and semantic foundations that enable trusted enterprise analytics and AI-driven data consumption.
Across 13+ years in SaaS and technology organizations, I have built business systems, data platforms, analytics engineering practices, governance forums, and self-service capabilities that help leaders make decisions from consistent and reusable information.
Faster analytics delivery
Modernized ELT and modeling practices to reduce analytics development and delivery time by approximately 80%.
Influenced revenue opportunities
Designed systems connecting product usage, account intelligence, and go-to-market execution.
Technology budget
Managed systems technology portfolio and operating budget across business applications and GTM platforms.
Technology-spend ROI improvement
Improved technology-spend ROI through portfolio management, consolidation, and better operating discipline.
AI-ready metric consumption
Delivered a Cube semantic layer exposing governed metrics through Model Context Protocol for AI and analytics consumption.
AI-ready data architecture
Trusted enterprise information has to be designed before it can be automated.
I build the connective tissue between governed data assets, business definitions, BI tools, AI agents, conversational analytics, and operational applications.
Governance
Metrics that mean the same thing everywhere
Definitions, ownership, quality expectations, and reusable models create the trusted source of truth that executives, operators, dashboards, and AI systems can share.
Semantics
Semantic layers as an enterprise interface
A governed semantic layer turns warehouse logic into discoverable business concepts, reducing metric drift and making self-service consumption safer.
AI consumption
AI needs governed context, not just data access
AI agents and LLM-powered applications are most useful when they retrieve approved metrics, definitions, and context through controlled interfaces such as Model Context Protocol.
Leadership and operating model
Operating discipline that turns data teams into durable platforms.
I lead by creating clarity: clear definitions, clear ownership, clear delivery standards, and clear operating rhythms. The goal is to help teams move faster while preserving trust in the metrics, systems, and decisions they support.
- Start with the business decision and work backward to the metric, model, system, and operating process required to support it.
- Treat governance as an enablement system: lightweight enough to use, strong enough to prevent inconsistent definitions and low-trust reporting.
- Build reusable platforms and standards so analytics engineers, data engineers, analysts, and business partners can compound each other's work.
- Lead multidisciplinary teams with explicit ownership, practical documentation, and delivery habits that make quality repeatable.
Career progression
From engineering systems to data and analytics leadership.
Experience across SaaS organizations, business systems, data architecture, analytics engineering, governance, and revenue technology.
2024 — Present
Manager, Business Intelligence & Analytics Engineering
Jobber
Leads BI and analytics engineering across self-serve analytics, governance, executive reporting, semantic layer patterns, and AI-ready metric consumption.
2024
Manager, Data & Analytics
Backlight
Managed data engineering and analytics modernization, implementing ELT architecture and modeling standards that accelerated delivery.
2016 — 2023
Senior Manager, Architect, and Technical Roles
Vidyard
Progressed through technical support, systems architecture, GTM systems, business applications, data architecture, machine-learning capabilities, and revenue systems leadership.
2011 — 2016
Engineering and Technical Foundations
Jabil Circuit and Ooyala
Built early foundations in engineering design, technical support, systems thinking, and customer-facing problem solving.
Selected work
Architecture tied to outcomes
Non-confidential examples of governed platforms, analytics modernization, and business systems that created operating leverage.
Governed semantic layer
Architected an enterprise Cube semantic layer that exposes governed metrics through Model Context Protocol for AI agents, conversational analytics, LLM-powered applications, and dashboards.
Read case studyAnalytics modernization
Implemented ELT and modeling standards that reduced delivery time by more than 80% in the first few months.
Read case studyRevenue systems architecture
Designed GTM and product-led systems tied to more than $15M in ARR opportunities.
Read case studyTechnology and architecture experience
Modern data stack, business systems, and AI enablement.
Data platforms and orchestration
- AWS
- Redshift
- Snowflake
- BigQuery
- Airflow
- Fivetran
Analytics engineering and semantics
- dbt
- Cube
- Tableau
- Looker
- Semantic modeling
- Metric governance
AI and application consumption
- Model Context Protocol
- AI agents
- LLM-powered applications
- Conversational analytics
- Workflow automation
Business and revenue systems
- Salesforce
- Reverse ELT
- GTM systems
- Product-led growth
- Technology portfolio management
Contact
Looking for a Director or Senior Manager to scale trusted data and analytics?
Connect with me for leadership opportunities focused on data platforms, analytics engineering, semantic layers, governance, conversational analytics, and AI-ready enterprise data.
Connect on LinkedIn