15+ years shaping data platforms at Workday, Lyft, and beyond — now building the layer above the dashboard: semantic models, self-healing pipelines, and AI decision systems like Pipeline Sentinel.
I started in BI when "analytics" meant Excel and Tableau. Fifteen years later, I'm building the layer above the dashboard — semantic models, agentic pipelines, and AI interfaces that turn governed data into executive decisions.
At Workday I lead BI Analytics and shipped an AI Companion that lets execs query marketing performance in natural language, grounded in our semantic layer. At Lyft I built the growth analytics stack behind multi-million-dollar acquisition spend. Before that: supply chain analytics at Intuitive Surgical, CRM transformation at Juniper.
The projects below are how I learn in public — each one is a production-grade system, not a notebook. If you're building the next generation of data/AI platforms, let's talk.
-- customer feedback analysis inside Snowflake SELECT customer_id, SNOWFLAKE.CORTEX.SENTIMENT(support_notes) AS sentiment, SNOWFLAKE.CORTEX.CLASSIFY( support_notes, ['billing', 'outage', 'feature'] ) AS category, SNOWFLAKE.CORTEX.COMPLETE( 'llama3-70b', CONCAT('Summarize: ', support_notes) ) AS summary FROM customer_feedback WHERE region = 'EMEA';
A newsletter for data engineers, analytics engineers, and data leaders navigating the shift to AI-native stacks. Grounded in what ships — not what's on the conference slide.
Shipped an AI Companion enabling natural language querying of enterprise marketing metrics — grounded in our semantic layer, with governed, context-aware responses. Built the AI-enabled executive summary engine synthesizing campaign performance into board-ready narratives (direct inspiration for the Marketing AI project). Led the Analytics Modernization Program — migrated Tableau to Sigma on Snowflake/dbt, established governed self-service for global Sales & Marketing. Institutionalized forecasting that reduced manual reporting ~40%. Led 8+ analysts & engineers.
Built the data infra behind multi-million-dollar marketing spend across acquisition channels. Designed campaign attribution, funnel analytics, and churn frameworks enabling data-driven budget reallocation. Owned CAC, ROI, retention, LTV metric definitions.
Modernized analytics in a regulated medical-device environment — migrated Excel processes to production pipelines and governed dashboards for efficiency, lead times, defect rates, and capacity planning.
Actively talking to teams building the next layer of the data stack — AI-native analytics, agentic DataOps, fintech data platforms, enterprise LLM infrastructure.