Washington DC-Baltimore Area
For 17 years I watched enterprises create unnecessary risk the same way — moving raw data to distribute value. Dashboards, spreadsheets, vendor feeds, AI pipelines. Every one a potential liability. Every one a compliance team's nightmare. I built Spartera around a single conviction: the data never has to move. Only the insight does. That architecture doesn't just reduce risk — it unlocks monetization that was never possible when sharing meant exposing. Whether you're distributing analytics internally, feeding AI agents with live structured data, or turning your proprietary data into external revenue streams, Spartera makes it possible without ever loosening your data governance posture. Building it has only sharpened what I already knew from 17 years in the field: most AI initiatives don't fail because the models are wrong. They fail because the data layer underneath was never built to support production-grade intelligence — and because nobody caught it before it landed on the risk register. That's where I come in as an advisor. When an enterprise AI initiative stalls, misfires, or becomes a liability — vendor can't deliver, board wants answers, the transformation that was supposed to create value is now creating exposure — I diagnose what went wrong, stabilize the architecture, and give leadership a defensible path forward. Previously: Senior AI Architect, Google Cloud ($50M+ revenue impact, 85% faster deployments) • Principal Analytical Lead, Google Travel ($700M+ portfolio) • Adobe • Omnicom/Annalect • PwC • M.S. Data Science, Northwestern — Summa Cum Laude, 4.0 GPA. If your AI initiative needs someone who has seen this before — and built the infrastructure to make sure it doesn't happen again: tonydiloreto.com
Every enterprise data problem I've ever seen had the same root cause: to distribute value, someone moved raw data. Into a dashboard. A spreadsheet. A vendor pipeline. An AI agent. Each one a governance risk hiding in plain sight. Spartera is the infrastructure I built to fix that. A zero-data-movement analytics marketplace where queries execute directly in your environment — only the insight leaves, never the data. The result: organizations can finally do two things they couldn't do safely before — distribute analytics internally without creating exposure, and monetize proprietary data externally without losing control of it. For data sellers: Turn locked data assets into API-accessible revenue streams. Your data stays where it is. Your buyers get the answers they need. You set the terms. For data buyers and AI teams: Access governed, deterministic analytics across 17+ platforms — BigQuery, Snowflake, Databricks, Redshift and more — without the compliance overhead of raw data acquisition. 14,000+ analytics products. Zero data movement.
Drove $50M+ in new revenue for Google Cloud by designing and deploying AI pipeline architecture that cut customer deployment time by 85%+. Managed and mentored a team of 8 AI engineers. Projected 1–2% annual revenue growth for a national grocer’s digital business through a custom ML-powered recommendation engine. Reduced infrastructure costs 30%+ for a leading media company by rearchitecting their cloud data warehouse and AI environment. Served as the technical bridge between C-level strategy and engineering execution for Fortune 500 clients across retail, media, healthcare, and financial services.
Consulted C-level executives at Fortune 500 companies, saving clients tens of millions in technology costs by redesigning legacy infrastructure on Google Cloud Platform. Led the re-architecture of the world’s largest media agency’s global digital analytics platform — ingestion, storage, and processing — reducing time to insight and total operating costs. Grew one retail customer’s digital sales 15% through improved recommender systems. Reduced IT expenses 50%+ by leading the design and rollout of a leading retailer’s entire data warehouse infrastructure, managing national teams of consultants and architects.
Improved key digital performance metrics (CTR, CVR, AOV) for Google’s largest travel advertisers through innovative analytical models, increasing platform loyalty and advertising revenue. Co-delivered new cloud-based analytical systems across Google’s analyst organization, unlocking millions in net new customer spend and reducing time to decision for business leaders.
Directed the rollout and enhancement of Omnicom’s enterprise Data Management Platform, overseeing all strategic AdTech integrations for media planning and buying. Led technical presentations to prospective and existing clients, contributing to tens of millions of dollars in new business. Managed a cross-functional team of analysts, managers, and data scientists.
Developed behavioral optimization algorithms and predictive models that saved enterprise retail clients millions in marketing and research costs. Architected cross-channel digital marketing campaigns for Fortune 500 companies. Supported data science initiatives that helped a leading global telecom save hundreds of thousands in annual advertising spend through improved visitor targeting and personalization strategy.
Data warehousing, ETL, and analytics reporting for enterprise clients. Early career foundation in consulting, financial systems, and client management.