Business Operations & Automation Leader
Business Operations & Automation Leader · FinOps & Cloud Cost · Intelligent Automation & AI Operations · Revenue Operations / GTM · Chief-of-Staff Scale.
I build the mechanisms that make enterprise performance repeatable — not dependent on individuals.
I · Profile
A business-operations and automation leader with a nearly thirty-year record of running, building, and growing the operating engine of global technology businesses — and automating the parts that shouldn't depend on people. Nine years at Amazon Web Services leading business operations, automation, and the executive operating cadence for a global services business; more than a decade at Bloomberg in platform engineering and analytics leadership; rooted in early industrial-automation and IT/OT work. The throughline is operations and automation: find the root problem, design the system or operating model that solves it at scale, and hold the organization accountable to outcomes over activity. Fluent end to end in the revenue motion — pipeline health, forecast accuracy, customer lifecycle — and in the FinOps discipline, AI operations, and executive operating cadence required to run it globally.
Portfolio · Moments Worth Telling
AWS Global Services had field data everywhere and insights nowhere. I was handed a whiteboard and told to fix it. What came back was the Insights Hub — AWS’s first centralized analytics platform for the field — along with the Insights Catalog, a bi-directional data framework, and a Data Confidence and Completeness Scoring system that made the data trustworthy enough to build on. The AI-ready data layer I designed became the foundation for predictive modeling and GenAI integrations across the org.
Bloomberg ran on infrastructure nobody could see clearly. Hundreds of operational systems held pieces of the picture — CMDBs, ticketing platforms, monitoring tools — but nothing reconciled them into a single source of truth. I built that system from scratch: a unified platform that ingested, reconciled, and surfaced the full lifecycle of Bloomberg’s infrastructure estate. The engineering org ran on it. Nothing like it had existed before.
Leadership can’t run a global business on gut feel. I designed the KPI architecture, data dictionaries, and WBR/MBR/QBR review mechanisms that AWS Global Services used to manage performance — from the field up to the C-suite. When the weekly business review ran, the data it ran on was mine.
The global TAM organization had no systematic way to see which customers were healthy and which were at risk. I built one. Starting with the analytics team standup, I engineered the first customer health scoring and churn-risk models the field had ever had — giving leadership a data-driven view of renewal and risk that changed how account teams prioritized their time.
Bloomberg’s Windows estate ran on legacy provisioning that couldn’t keep pace with the organization’s growth. I led the Active Directory modernization and the global virtualization program — heading a 30+ engineer team that replaced manual processes with automated, scalable infrastructure across Bloomberg’s worldwide environment.
When I took over Global Linux Engineering, Bloomberg provisioned servers by hand. I built the private cloud that changed that — architecting the automation layer, standing up the CMDB and telemetry platforms, and scaling the Linux estate from a small footprint to tens of thousands of hosts globally. By the time I moved on, manual provisioning was a memory.
A newspaper never stops. The presses run overnight, and when something breaks at 2am, someone has to know what to do. I owned the IT and PLC systems for a continuous print manufacturing operation — server infrastructure, AGV control, production automation, and real-time fault response across the plant floor. I kept the operation running.
The TAM teams covering Financial Services, Healthcare, Media & Entertainment, and Government had no unified view of their business. I built the revenue-operations framework, the P&L dashboards, and the analytics infrastructure that changed that — giving field leadership real-time visibility into performance, churn risk, and renewal health for the first time.
Enterprise Support was growing faster than the operating model could keep up. I built the structure that caught up with the scale — a hub-and-spoke segmentation model, customer prioritization and tiering frameworks, and a multidisciplinary team assembled from scratch: PMs, business intelligence engineers, data scientists, TPMs, and curriculum developers. I stood up the function and defined how it ran.
Amazon’s Bar Raiser program is an invitation you earn, not apply for. It recognizes the handful of leaders whose judgment on hiring is trusted enough to hold the bar across levels and functions. I earned the designation and served on hiring panels across the organization — not just for my own team, but wherever the standard needed keeping.
When Enterprise Support launched its manager-excellence recognition program, I was first. The award wasn’t applied for — it was given. It reflected the team culture, the development practices, and the leadership model I’d built inside the org over years. First in the program’s history.
My town’s historic preservation committee reviewed city council agendas by hand — downloading PDFs, looking up block-and-lot numbers, cross-referencing zoning maps. I automated it. A pipeline that pulls meeting materials from the city portal, resolves every property reference to a real address, checks it against historic district boundaries, and assembles everything into a clean HTML briefing. The first time the board used it, the response was: “This is great.” Built evenings. Shipped July 2026.
II · Expertise
Intelligence systems and executive operating cadences leadership runs the business on.
Data-confidence layers and business-insight platforms that make decisions trustworthy at scale.
Cloud cost strategy built into the operating model, not bolted on afterward.
Pipeline health, forecast accuracy, and customer lifecycle — the full revenue motion, run as a system.
Building functions from a founding team into global, multidisciplinary organizations.
Platform migration and infrastructure modernization at enterprise scale, with zero disruption.
Full transformation of global sales and services organizations without slowing them down.
KPI frameworks, data dictionaries, and the C-suite review rhythms leadership decides by.
III · Experience
New York Metro · Hybrid
Business-operations leadership, AI-native automation, executive operating cadence, and data-confidence governance.
Chief-of-staff scope; annual operating plan; GTM feedback loop; executive cadence.
Org build, capacity planning, KPI scorecards, global transformation.
Revenue-operations framework across Financial Services, Healthcare, Government, Media & Entertainment, and high-growth SaaS; first-ever manager-excellence recognition; Bar Raiser.
Regulated-environment cloud/hybrid architecture.
New York, NY
Built Bloomberg’s first unified intelligence platform — the intellectual predecessor to the data-confidence approach later formalized at AWS — normalizing data from many independent source systems into one authoritative record for leadership planning and capacity decisions.
Bloomberg is 24/7, 365. The Terminal never goes down — it can't. Financial markets don't pause, and the infrastructure underneath them doesn't get maintenance windows. I architected and executed the migration of the Bloomberg Terminal from legacy proprietary systems to commodity Linux infrastructure at global enterprise scale — scaling a fleet spanning tens of thousands of hosts worldwide, building automated provisioning for rapid deployment, and doing all of it without a single moment of production disruption. The Terminal kept running. It always kept running.
Before leading engineering, I built the tools and operational patterns the team ran on — directory-services consolidation, virtualization, enterprise software distribution across Bloomberg's global footprint. All of it against the same constraint that defined every Bloomberg project: 24/7, 365, no exceptions. You learn to build differently when there's no such thing as a safe time to take something offline.
New York, NY
The Daily News ran presses through the night, every night. Editorial closed, the building quieted, and production took over — plates made, ink running, papers moving out the door before the city woke up. I owned the full IT estate that kept it going: servers, networking, the PLC systems that controlled the production floor, and the AGV infrastructure that moved materials through the plant. Overnight production meant overnight problems. Something goes down in the middle of a press run, you fix it — no escalation path, no morning ticket queue, just you and a system that has to be back up before the next edition is late. Six years of that builds an instinct for operational reliability that never leaves you. It's where I first understood that technology exists to keep something else running, and that the people responsible for it have to understand what that something else is.
New York Metro
Started on the ground, in the most literal sense — running cable, racking servers, and deploying workstations and networks in government offices and public schools across the New York metro area on IBM public-sector contracts. Every site was different. Every configuration had to work before you left. No one to call, no second visit scheduled — you either made it work or you didn’t. It was field engineering at its most unforgiving, and it taught me something that years of management later only confirmed: the people who understand the stack from the wire up see things that everyone else misses. This is where I became one of those people.
IV · Credentials
Certifications
Education
V · Civic Leadership
Aimone Advisory
Aimone Advisory helps enterprise and growth-stage technology companies build the operating backbone that makes performance a system, not a heroic effort — business operations, FinOps, AI-readiness and data governance, and GTM.
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