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Microsoft Fabric, Azure, SQL
Confidence in decision-making
Distributed teams, stakeholder alignment
Executive positioning for leadership roles in data & analytics, platform modernization, and governance.
Short bio for speaking, board, or partner introductions.
Modernizing platforms, strengthening governance, and delivering measurable outcomes in regulated environments.
For more than two decades, I have led the design and modernization of enterprise data platforms supporting complex financial and operational environments. Most recently, I directed data engineering strategy within a $150B asset management platform, aligning trading, accounting, and security master domains under scalable architectural and governance frameworks.
My focus extends beyond technical delivery to platform stewardship. I lead modernization initiatives that strengthen reliability, reduce reporting latency, improve auditability, and enable faster decision-making across the enterprise. From lakehouse adoption and semantic modeling to SLA hardening and cross-geo team leadership, my work centers on building durable data operating models that scale.
Enterprise data platforms must be resilient, governed, and extensible — not merely functional. Strategy only matters when it produces measurable outcomes.
Enterprise outcomes delivered through platform modernization, governance, and operating discipline.
$150B
Platform responsibility
Directed enterprise data strategy supporting a $150B asset management platform.
4
Major platform implementations
Delivered three enterprise data warehouses and one cloud lakehouse/warehouse implementation to accelerate trusted analytics at scale.
Modernization
Transformation delivery
Delivered modernization across lakehouse/warehouse patterns with governance focus.
Lower latency
Reporting responsiveness
Reduced reporting latency by modernizing pipelines and enabling semantic models.
Directed enterprise data engineering strategy for a $150B platform, aligning modernization initiatives with governance and executive priorities.
Operationalized curated data layers and semantic models to reduce reporting latency and speed decision-making.
Improved data completeness and SLA resilience by moving key workflows to secure, API-driven acquisition and automation.