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Global Payments Inc. · 1 day ago

Head of Enterprise Data Engineering

Alpharetta, GA

Full-time

Hybrid

Director/Executive

15+ years exp

Global Payments Inc. is seeking a Head of Enterprise Data Engineering to define and execute the enterprise data engineering strategy for AI-ready data at global scale. This role involves leading the architecture and operations of modern cloud data platforms, establishing trusted data domains, and partnering with various leaders to enhance data-driven outcomes across the enterprise.

AppsBankingCreditEnterpriseFinanceFinancial ServicesPayments

Responsibilities

Define and own the enterprise data engineering strategy and reference architecture for AI-ready data, including cloud platform, data products, and automation-first delivery model. Develop and communicate the enterprise data strategy and roadmap, ensuring alignment with business transformation, regulatory needs, and future-proofing

Lead architectural decisions for lakehouse patterns, streaming, CDC, and event-driven integration; balance reuse, performance, cost efficiency, and time-to-market

Architect, implement, and operate hybrid and cloud-native data platforms with heavy automation

Establish trusted domains focusing on security, governance, and reuse across business lines.Lead the design and delivery of reusable, trusted data products with clear SLAs, documentation, versioning, and APIs; enforce data contracts between producers and consumers

Enable secure, governed data sharing and monetization where appropriate

Provide platform services and reusable capabilities for data science and AI: feature store, model-ready curated layers, governed sandboxes, MLOps integration, and model/data lineage

Embed data governance within pipelines: lineage capture, data classification, role-based and attribute-based access, fine-grained controls, and consent management. Implement DQ-by-design: thresholding, anomaly detection, reconciliation, and data SLAs enforced in CI/CD and runtime with automated quarantine/retry/escalation

Manage a multi-million-dollar budget by optimizing build-vs-buy decisions, licensing, cloud spend, and vendor relationships. Scale teams and partners globally while building strong relationships with executives, technical teams, vendors, and business partners to understand needs, influence strategy, and promote best practices

Oversee large-scale data migration, modernization, and platform implementation projects, balancing innovation, cost-effectiveness, and risk management

Scale, mentor, and inspire a diverse, high-performing data engineering and architecture team; develop adaptive hiring and resourcing strategies reflecting organizational growth and transformation

Ensure compliance with all risk, regulatory, and audit standards, and maintain rigorous internal controls

Qualification

Data architectureCloud-native platformsData governanceReal-time data streamingAI/ML integrationData modelingData integrationChange data captureMLOpsPeople leadershipExecutive presenceCommunication skillsStrategic thinkingTeam mentoring

Required

15+ years in engineering and/or data and analytics, including 8+ years leading large-scale data engineering and platform teams in complex, regulated environments

Deep expertise in data architecture and engineering: data modeling (OLTP/OLAP), big data and query engines, lakehouse, data warehousing, MDM, data integration, CDC, and large-scale batch/stream processing

Experience delivering data products at scale with embedded governance, metadata/lineage, and continuous DQ; strong background in data contracts and data observability

Real-time data streaming expertise (e.g., Kafka, Pub/Sub, Kinesis), event-driven architectures, and change data capture patterns

Proven success designing and operating enterprise cloud-native data platforms on at least one hyperscaler

Practical experience enabling AI/ML: feature stores, model-ready datasets, MLOps integration, and privacy-preserving patterns; comfortable partnering with data scientists and ML engineers

Executive presence with the ability to translate complex architectures into business value, present to senior leadership/board-level stakeholders, and lead through influence

Bachelor's or Master's degree in Computer Science, Engineering, or related discipline (STEM preferred)

5+ years of people leadership, including hiring, performance management, coaching, and org design

Preferred

Experience in payments, fintech, or financial services with knowledge of domains such as merchant onboarding, transaction processing, settlement, chargebacks, fraud/risk, and regulatory reporting

Familiarity with data monetization, secure data sharing, and embedded analytics patterns for partners/merchants