Diamond (Williams) Nwankwo is a Data Governance and Data Quality Leader who has spent her career in the environments where bad data has physical consequences: aerospace quality systems, manufacturing operations, and federal data programs. Her foundation is industrial and quality engineering, and it defines her method. She applies FMEA, Six Sigma, and lead-auditor discipline to data, measuring defects before governing them and building programs designed to survive an audit.

Most recently she built the enterprise data and AI governance program at PAR Technology, taking it from no framework to an operating function: a governance model with named domain owners and stewards, a cross-functional governance council, Microsoft Purview as the system of record for metadata and lineage, data quality scoring across Salesforce and downstream analytics, and an executive command center in Power BI that made governance measurable to leadership.

Before PAR, she served a two-year term as a GS-15 Emerging Technology Fellow with xD at the U.S. Census Bureau, contributing to enterprise database modernization and AI governance initiatives and co-authoring Responsible Artificial Intelligence in the U.S. Federal Government: Principles, Policies, and Practices. Her earlier work, Data Quality Management in Industry 4.0, was published in ASQ's Software Quality Professional.

She is an Adjunct Instructor in Maryville University's graduate Data Analytics program, where she designs and teaches courses in data analytics and data management.

She holds an M.S. in Quality Management from Eastern Michigan University and a B.S. in Industrial Engineering from Missouri University of Science and Technology. Her credentials include ISO/IEC 42001 Lead Implementer, ISO 8000 Master Data Quality Manager, AS9100/ISO 9001 Lead Auditor, Lean Six Sigma Green Belt, and multiple Microsoft Azure certifications.

Today, her mission remains centered on building data and AI ecosystems where engineering, quality, auditing, risk, and governance eliminating silos. Therefore, supporting reliable decisions and meaningful outcomes. She creates data foundations that leaders can trust and teams can depend on, because when data is well-managed from end to end, everything else becomes possible.