Adobe Experience Platform at the core, plus Tealium Data Hub, measurement, tracking, and consent. Barcelona and remote.
Open to contract roles and consulting engagements. I also consider selected permanent roles with a strong technical scope.
Problems that look like platform issues and are usually architecture, data or operating issues.
AEP is live, but identity does not resolve and every use case uncovers another exception.
Web, apps, analytics, and activation collect different data, or consent does not reach the destination.
You are comparing a suite with composable or warehouse-native options and need to decide before signing.
MarTech implementations stall when the data model, collection, identity, and consent evolve separately.
I work from architecture through configuration: CDPs and journeys, web and app measurement, Tealium, server-side delivery, and governance. Then I document the result so your team can operate it.
Customer data flow diagram. On the left, collection, with two cadences: web and app and server events as streaming, CRM and core systems and historical loads as batch. In the center, the identity contract and consent, which all data from the four sources passes through. Then the unified profile with its audiences and its state, and below it Decisioning, which resolves the next best action. On the right, activation: journey analytics reads from the profile; journeys and campaigns and destinations and media come out of Decisioning.
Four highlighted engagements from a broader offer. Each has a defined start, deliverable, boundaries, and next step.
I assess an existing MarTech implementation and turn the observed problems into prioritized findings and a remediation plan.
I build one complete use case, from the agreed source through to an activation or journey that the team can operate.
I design or rebuild data collection across web and apps so events, identities, and documentation follow the same contract.
I compare requirements with real capabilities and expose the integration, operating, and ownership trade-offs before recommending an option.
Anonymized projects, architecture decisions, and public analysis let you review how I work.
Two data and architecture projects presented anonymously to preserve confidentiality.
The organization did not have a CDP. The project had to introduce AEP as a shared data, orchestration, and personalization layer, and deliver a working MVP first. The architecture had to support historical loads, real-time events, and later evolution without rebuilding the foundation.
Measurement was split across the public site, the logged-in area and the app, each with its own implementation. Without a common data layer, neither reporting nor activation could be trusted.
Market analysis · LinkedIn
An analysis of nine MarTech stack patterns, from the integrated suite through composable and warehouse-native.
Seven visual notes on the decisions that fail after launch: identity contracts, shared profile state, channel reuse, Decisioning and operational handover.
Four short technical reviews that order what to look at first. They run in your browser, send no answers, and ask for no email.
Ordered by what I have implemented, not by what I have seen.
Banking and insurance in recent years. Before that, retail, fashion, education, travel, entertainment, consumer goods, and automotive. Always large organizations, identified by sector.
The initial consultation is free: a 20-minute conversation to see whether I am a fit and what the next step should be.