Head of Data & AI Architecture

Global Payment Holding Company • Atlanta, GA

1d

About The Position

Every day, Global Payments makes it possible for millions of people to move money between buyers and sellers using our payments solutions for credit, debit, prepaid and merchant services. Our worldwide team helps over 3 million companies, more than 1,300 financial institutions and over 600 million cardholders grow with confidence and achieve amazing results. We are driven by our passion for success and we are proud to deliver best-in-class payment technology and software solutions. Join our dynamic team and make your mark on the payments technology landscape of tomorrow. Ready to take your career global? Make your mark at one of the biggest names in payments. We’re looking for a leader who can build a unified, trusted, and governed data foundation to create reusable, domain-driven data products that power analytics, AI, and merchant-centric solutions. The Head of Data & AI Architecture owns the architecture that makes this real. Reporting to the Head of Data Strategy within the Office of the Chief Data Officer, this leader translates our Data & AI strategy and the broader business strategy into concrete, target-state designs. What our data platforms, data products, models, and (Gen)AI solutions should be, and how they fit together will be part of this leaders mandate. Partnering with the enterprise architecture function, this role goes deep in the data and AI domains defining the reference architecture, solution blueprints, and design standards that engineering and delivery teams build against, and grounding every decision in security, governance, and measurable business outcomes. This leader will champion a platform centric approach to Data & AI, establishing reusable architectural patterns, self-service capabilities, and Data & AI Platforms as a Service that enable business domains to rapidly create, discover, govern, and consume trusted data products, analytics assets, and AI solutions.

Requirements

• 12+ years of experience in data and technology architecture, including 5+ years leading enterprise-scale Data and AI architecture initiatives.
• Proven track record in domain and solution architecture, defining target-state architectures and reference designs within complex, regulated environments.
• Deep expertise in modern data platforms, including cloud data warehouses, lakehouses, streaming architectures, data modeling, and domain-driven data products.
• Hands-on experience architecting AI/ML and GenAI solutions at scale, including MLOps, LLMOps, RAG, and agentic AI capabilities.
• Strong foundation in data governance, security, privacy, and regulatory compliance, including PCI DSS and data protection requirements.
• Advanced knowledge of cloud-native data and AI services, with deep expertise in AWS, Azure, or Google Cloud.
• Experience designing and implementing MDM, reference data, metadata management, lineage, and semantic-layer architectures.
• Demonstrated ability to influence engineering, product, and business teams, building alignment around architectural strategy and standards.
• Bachelor’s degree in Computer Science, Engineering, or a related field required; advanced degree preferred.
• Proven experience building, leading, and scaling architecture teams in large, complex, global organizations.
• Demonstrated success leading through influence in highly matrixed environments where outcomes require alignment across multiple stakeholders and organizations.
• Exceptional executive communication, presentation, and storytelling skills, with the ability to tailor messages from technical teams through C-suite audiences.
• Strong people leadership experience, including talent acquisition, coaching, performance management, succession planning, and organizational development.
• Demonstrated ability to drive organizational change, establish new operating models, and lead enterprise transformation initiatives.
• Experience facilitating executive steering committees, architecture review boards, and technology governance forums.
• Proven ability to communicate complex architecture and AI concepts in business terms that drive strategic decision-making and investment prioritization.
• Experience designing and operating enterprise-scale platform architectures that provide Data, Analytics, and AI capabilities as reusable services.
• Demonstrated success establishing self-service data and AI ecosystems that enable domain teams to independently develop and consume governed data products.
• Strong understanding of platform engineering principles, internal developer platforms, reusable architecture patterns, and product-oriented operating models.
• Experience implementing cloud-native data and AI platforms that emphasize automation, standardization, and developer productivity.

Nice To Haves

• Experience in payments or fintech, with a strong understanding of sensitive financial and payment data environments.
• Proven success leading large-scale platform integrations, modernization programs, and post-merger technology rationalization efforts.
• Industry-recognized certifications in cloud architecture and enterprise architecture frameworks such as TOGAF are highly desirable.
• Experience establishing and operating modern data organizations, including domain ownership models, data mesh, and federated governance frameworks.
• Experience leading globally distributed architecture, engineering, and data teams across multiple regions and time zones.
• Experience establishing architecture Centers of Excellence (CoEs), Communities of Practice, and architecture governance programs at enterprise scale.
• Executive presence with a demonstrated ability to engage and influence C-suite leaders, board-level stakeholders, and external partners.

Responsibilities

• Own and evolve the target-state Data & AI architecture, translating strategy into scalable solutions aligned to business and technology priorities.
• Define reference architectures, standards, and reusable design patterns across data platforms, analytics, ML, GenAI, and agentic AI.
• Architect the enterprise data product model, including domains, MDM, semantic layers, and governed reusable data assets to enable a build-once, reuse-everywhere approach.
• Design end-to-end AI ecosystems spanning feature stores, model development, MLOps/LLMOps, RAG, and agentic frameworks at enterprise scale.
• Establish integration patterns that connect source systems, data products, analytics, and AI into a unified, governed architecture.
• Embed security, privacy, responsible AI, and regulatory requirements into architecture by design.
• Partner closely with Enterprise Architecture to align Data & AI capabilities with enterprise standards and target architecture principles.
• Provide hands-on architectural leadership to engineering and platform teams, guiding solution design and key technical decisions.
• Lead platform and technology strategy, driving build, buy, and partner decisions with clear business and technical rationale.
• Establish architecture governance through standards, design reviews, and decision frameworks that enable speed, consistency, and resilience.
• Drive modernization and simplification by defining cloud-native, AI-ready architectures and eliminating duplication across the technology landscape.
• Build and mentor a high-performing architecture team while serving as a trusted advisor to Data & AI and enterprise technology leadership.
• Build, lead, and develop a high-performing team of Data & AI architects, fostering a culture of innovation, accountability, continuous learning, and engineering excellence.
• Coach, mentor, and develop architects and technical leaders, creating clear career paths and succession plans for critical architecture capabilities.
• Serve as an influential communicator and change agent, translating complex technical concepts into clear business outcomes for executive, technology, and business stakeholders.
• Build strong partnerships across Product, Engineering, Enterprise Architecture, Security, Risk, Compliance, and business domains to drive alignment and execution.
• Lead through influence in a matrixed environment, establishing trust and credibility across multiple lines of business and technology organizations.
• Drive organizational adoption of architectural standards, data product principles, AI governance, and best practices through effective communication and stakeholder engagement.
• Facilitate executive-level architecture reviews, strategy sessions, and investment discussions, providing clear recommendations and decision frameworks.
• Champion a culture of collaboration, transparency, and continuous improvement across Data, AI, and technology teams globally.
• Develop and communicate a compelling Data & AI architecture vision, roadmap, and strategy that aligns technical investments with measurable business outcomes.
• Act as a trusted advisor to senior executives, helping shape enterprise-wide decisions related to data, analytics, AI, and technology modernization.
• Define and institutionalize reusable architecture patterns, reference implementations, and accelerators that enable rapid and consistent delivery of data products, analytics, and AI solutions.
• Establish and evolve Data & AI Platforms as a Service, providing self-service capabilities, standardized tooling, and reusable components that enable teams to build and consume data and AI solutions at scale.
• Create standardized architecture blueprints for common use cases, including data ingestion, data sharing, semantic modeling, feature engineering, GenAI, RAG, agentic AI, and model deployment.
• Drive a platform-first operating model that reduces bespoke solutions and promotes reuse, consistency, and operational efficiency across the enterprise.
• Define enterprise-wide standards for data product development, metadata management, semantic layers, and AI solution patterns to enable a build-once, use-many (fan out) approach.
• Establish architecture guardrails and paved-road solutions that balance governance, security, and compliance with agility and self-service.
• Promote Data Products, AI Products, and Platform Products as foundational building blocks of the enterprise Data & AI ecosystem.
• Establish reference architectures and patterns that support multi-cloud interoperability, open data architectures, and enterprise-scale reuse.

Benefits

• The people, the energy, the connections – it’s unmatched. Come and be part of an ever-evolving company and get dynamic opportunities that go beyond borders.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior