Head of Data Governance & Enablement Platforms

Global Payment Holding Company•Alpharetta, OH

About The Position

Global Payments is seeking a leader to build a unified, trusted, and governed data foundation to create reusable, domain-driven data products that power analytics and AI. The Head of Data Governance & Enablement Platforms is responsible for the strategy, engineering, operation, and adoption of enterprise platforms that enable trusted, governed, and discoverable data at scale. This role owns the portfolio of governance enablement capabilities, including Data Catalog, Data Dictionary/Business Glossary, Metadata Management, Data Lineage, Master Data Management (MDM), Reference Data Management (RDM), Data Quality, Data Profiling, and Governance Workflow Automation. These capabilities are crucial for ensuring enterprise data is discoverable, understandable, trusted, compliant, and reusable. The leader will establish these capabilities as enterprise platform products, delivering self-service experiences and automated controls. This role collaborates with various teams including Data Trust & Risk, Data Strategy & Architecture, Data Engineering, Security, Risk, and Compliance to operationalize governance requirements through modern technology platforms. The objective is to create trusted data foundations that accelerate analytics, AI innovation, operational excellence, regulatory compliance, and business value realization.

Requirements

12+ years of experience in Data Management, Data Governance Technologies, Data Platforms, Data Engineering, or related technology leadership roles.
5+ years leading enterprise-scale implementations of Data Governance, Metadata Management, MDM, Data Quality, or Data Platform initiatives.
Proven experience implementing and operating enterprise Data Catalog, Metadata Management, Data Lineage, MDM, RDM, and Data Quality platforms.
Deep expertise with leading governance and metadata technologies such as Collibra, Alation, Atlan, Informatica, Reltio, or equivalent solutions.
Extensive experience designing and implementing enterprise Master Data Management and reference data solutions.
Strong expertise in metadata management, business glossaries, semantic models, data lineage, classification, and cataloging capabilities.
Demonstrated success implementing enterprise data quality frameworks, observability capabilities, profiling solutions, and quality management processes.
Experience implementing governance workflow automation, issue management, findings management, or stewardship, in support of enterprise governance programs.
Experience operating governance and enablement capabilities in cloud based data environments.
Strong understanding of modern data platforms, lakehouses, data warehouses, analytics ecosystems, and data product architectures.
Working knowledge of regulatory, compliance, privacy, and security requirements within highly regulated environments.
Proven ability to partner with governance organizations to operationalize policy through technology and automation.
Demonstrated experience leading platform engineering, product management, or shared services organizations.
Strong product mindset with experience managing technology platforms as products serving internal customers.
Exceptional communication, executive presentation, and stakeholder management skills.
Demonstrated ability to influence outcomes across complex, matrixed organizations.
Proven experience building, developing, and leading high performing technology teams.
Strong strategic thinking, analytical, and problem-solving capabilities.
Bachelor's degree in Computer Science, Information Systems, Engineering, Business, or a related field required.
Applicant must be authorized to work in the U.S. without the need for employment-based visa sponsorship now or in the future.
We will not sponsor applicants for U.S. work visa status for this opportunity.

Nice To Haves

Experience within payments, fintech, banking, or other highly regulated financial services industries.
Expertise with public cloud platforms including AWS, Azure, and Google Cloud.
Industry recognized certifications in Data Management, Governance, Cloud Architecture, or Platform Engineering disciplines.
Experience modernizing enterprise metadata, data quality, and MDM ecosystems in large global organizations.
Proven success establishing enterprise scale governance technology adoption programs and Centers of Excellence.
Experience implementing automated governance, metadata driven operations, and platform engineering practices.
Experience supporting regulatory audits, compliance requirements, and risk management programs through governance technologies.
Executive presence with demonstrated ability to influence senior business, technology, risk, compliance, and operations leaders.

Responsibilities

Own the enterprise strategy, roadmap, investment planning, and adoption of Data Governance & Enablement Platforms.
Lead the vision, implementation, modernization, and operation of enterprise Data Catalog/Business Glossary, Data Dictionary, Metadata Management, Data Lineage, Master Data Management (MDM), Reference Data Management (RDM), Data Quality, and Data Profiling platforms.
Establish governance enablement capabilities as enterprise platform products with clear business outcomes, service offerings, adoption targets, and reliability objectives.
Develop platform roadmaps aligned to enterprise Data, Analytics, and AI strategies.
Drive platform standardization, simplification, scalability, and automation across the enterprise.
Establish platform operating models, service management processes, SLAs, SLOs, and support frameworks.
Lead platform and technology decisions, including build, buy, and partner evaluations.
Manage platform budgets, vendor relationships, licensing strategies, and technology investments.
Own enterprise Metadata Management, Data Catalog, Business Glossary, Data Dictionary, and Data Lineage capabilities.
Establish metadata driven processes that improve discovery, understanding, trust, governance, and reuse of enterprise data assets.
Partner with Data Trust & Risk to define enterprise metadata, glossary, classification, and semantic standards.
Deliver self-service experiences that enable business and technical users to efficiently discover and consume trusted data products.
Establish lineage capabilities that provide end to end visibility across source systems, data pipelines, data products, and analytics assets.
Define and execute the enterprise Master Data Management (MDM) and Reference Data Management (RDM) platform strategy, roadmap, and operating model.
Partner with business stakeholders, Data Trust & Risk, and data domain owners to establish shared MDM and RDM services.
Enable the standardization, consistency, governance, and quality of master and reference data across the enterprise.
Establish and integrate MDM capabilities that support operational systems, data products, analytics, reporting, AI, and regulatory use cases.
Partner with business domains to define authoritative data sources, golden record strategies, survivorship rules, and data lifecycle management processes.
Implement scalable MDM capabilities, including entity resolution, hierarchy management, relationship management, and reference data administration.
Own enterprise Data Quality and Data Profiling platforms and services.
Establish self-service data quality capabilities, monitoring frameworks, observability solutions, and quality controls across critical enterprise data assets.
Enable proactive data profiling, anomaly detection, root cause analysis, and issue management capabilities.
Partner with Data Engineering and Data Product teams to embed quality controls throughout the data lifecycle.
Drive continuous improvement initiatives that increase trust and confidence in enterprise data.
Partner closely with the Head of Data Trust & Risk to operationalize governance policies, standards, and controls through technology platforms.
Implement governance workflows supporting data stewardship, certification, issue management, access, controls monitoring, and reporting.
Enable data contracts, metadata driven automation across the enterprise data ecosystem.
Establish automated enforcement mechanisms for metadata standards, data classification, retention policies, quality controls, and governance requirements.
Support regulatory, audit, privacy, security, and risk management requirements through platform capabilities and automation.
Partner with the Head of Data Strategy & Architecture and other Heads of Data Platform to align governance enablement platforms with enterprise architecture standards.
Partner with the Head of Data Engineering to ensure metadata, lineage, quality, and governance capabilities are integrated into enterprise data pipelines and products.
Deliver APIs, reusable services, and integration patterns that enable governance capabilities to be consumed across the enterprise.
Support data product adoption through trusted metadata, quality transparency, and discoverability.
Drive platform capabilities that improve data transparency, explainability, and trust.
Build, lead, and develop a high performing team of platform engineers, product managers, and governance technology specialists.
Foster a culture of innovation, accountability, customer focus, operational excellence, and continuous improvement.
Drive enterprise adoption through enablement programs, communications, training, and stakeholder engagement.
Establish strong partnerships with Data Trust & Risk, Data Strategy & Architecture, Engineering, AI, Security, Risk, Compliance, and business leadership teams.
Serve as a trusted advisor to senior leaders on governance enablement technologies, data trust, metadata strategy, master data management, and data quality modernization.
Communicate platform strategy, roadmaps, priorities, and outcomes to executive stakeholders and governance forums.
Champion the role of governance enablement platforms as foundational capabilities that increase trust, speed, reuse, and business value across the enterprise.