Experience

Leading enterprise AI analytics and engineering intelligence initiatives focused on AI adoption measurement and productivity evaluation across the SDLC.

• Lead GenAI productivity and AI analytics initiatives across the engineering organization.
• Own cross-functional AI telemetry and analytics strategy involving multiple AI coding providers and internal engineering platforms.
• Drive architecture decisions for scalable analytical systems supporting engineering intelligence and AI investment assessment.
• Partner with engineering leadership and executive stakeholders to define AI adoption measurement frameworks and productivity KPIs.
• Coordinate analytical initiatives spanning telemetry ingestion, data modeling, experimentation, and executive reporting.

Designed enterprise-scale data products supporting Observability, Governance, and Data Mesh initiatives.

• Led Data Mesh adoption and stronger data ownership practices across distributed teams.
• Built AI experimentation and analytics frameworks to measure the impact of Generative AI solutions.
• Designed ML systems, scalable feature store architectures, and analytical platforms supporting internal products.
• Developed data governance models and analytical initiatives improving operational visibility and executive decision-making.

Designed and implemented cloud-native data solutions supporting regulatory and business requirements.

• Translated complex Brazilian Central Bank requirements into production-grade systems.
• Built cloud-native ETL pipelines and Infrastructure-as-Code solutions using AWS services including Lambda and Glue.
• Designed a dynamic rule-based architecture capable of adapting to frequent business rule changes without modifying core logic.