Executive Data Leadership
Principal advisor for enterprise data management, responsible data culture, discoverability, accessibility, and the use of data as a strategic asset for mission outcomes.
Executive presence. Builder credibility.
I am the Chief Data Officer for the DHS OCIO, advising department leadership on enterprise data, AI, and mission technology. Before that, I spent years as a product engineer, architect, and delivery lead building software across financial services, pharmaceuticals, publishing, games, fashion, and government.
Positioning
Principal advisor for enterprise data management, responsible data culture, discoverability, accessibility, and the use of data as a strategic asset for mission outcomes.
Led and supported urgent public-sector systems including COVID vaccine tracking, family reunification websites, Operation Allies Welcome reporting, and human capital technology modernization.
Recent private work spans Cloud Run operations, iOS speech systems, on-device transcription, local network security scanning, email and data migration, Apps Script, BigQuery, OpenTelemetry, and AI-assisted workflows.
Work
Advises the CIO and department leadership on enterprise data management, AI/ML enablement, data discoverability, accessibility, and data-driven decision-making across the DHS mission.
Provided executive architectural guidance for information technology and human capital systems, led technical delivery for urgent government websites, and received DHS OCIO recognition for mission contributions.
Managed a technology team serving financial compliance clients, built hosted due-diligence and regulatory tools, contributed to the Big Data Committee, and delivered ML, Hadoop, MongoDB, MSSQL, C#/.NET, ETL, and rules platforms.
Designed enterprise web, mobile, CMS, data presentation, and role-based management systems across fashion, pharmaceuticals, publishing, games, and B2B mobile.
Private Code
Most of the strongest signal in my GitHub history is private. This site intentionally describes the shape of the work, not proprietary implementation details.
On-device and cloud-assisted transcription, model routing, private model asset handling, Gmail digest workflows, image recognition experiments, and AI-assisted operational tools.
Cloud Run jobs, resumable migration pipelines, verification queues, API benchmarking, calendar and mail synchronization, cutover runbooks, and production-oriented recovery flows.
Local network inventory, shadow AI fingerprinting, OpenTelemetry instrumentation, BigQuery-backed analysis, browser automation research, and command-center style dashboarding.
Mobile, server, and admin surfaces for product experiments, including backends, moderation/admin workflows, client apps, and deployment infrastructure.
iOS, Android, Swift packages, UI components, shared libraries, and platform-specific product surfaces.
Data quality tools, decision-tree experiments, financial/compliance-adjacent platforms, desktop utilities, and internal data editing workflows.
Technical Range
Operating Style
I can brief leadership, align stakeholders, and still read the stack trace, review the architecture, or build the proof-of-concept.
The most useful technology work is usually disciplined: clear ownership, boring deployment paths, explicit risks, and recovery plans that work when people are tired.
Data programs only matter when they change decisions, reduce friction, improve accountability, and make the right thing easier to do.
Public Work
Most repos are private, but these public repositories provide a few visible anchors for the older and open-source side of the portfolio.
Contact