Data Engineer, AI Governance

FIS Global is hiring a Data Engineer, AI Governance in Jacksonville, FL for an onsite role. In this position, you will design, build, and maintain data foundations that enable responsible, trusted, and scalable AI across the enterprise.

You will focus on backend data pipelines, governance, lineage, data quality, metadata management, and auditability, partnering with business and technology stakeholders to keep data reliable and compliant for both AI and analytics use cases.

Responsibilities

• Design, develop, and maintain scalable backend data pipelines, integrations, and data platforms that support AI governance and analytics initiatives.
• Consolidate and transform data from multiple enterprise sources into trusted, governed datasets for AI and business consumption.
• Establish and maintain end-to-end data lineage to provide visibility into data origins, transformations, and consumption.
• Collaborate with business, technology, and governance teams to define data ownership, stewardship, and accountability models.
• Implement data quality controls, monitoring frameworks, and observability practices to identify and resolve data issues proactively.
• Develop metadata management processes to improve discoverability, traceability, and governance compliance.
• Support data access governance by helping define, automate, and monitor data access controls and permissions.
• Build and maintain data validation, reconciliation, and audit capabilities to strengthen trust in enterprise data assets.
• Work with AI, machine learning, and analytics teams to ensure governed data is available for model development and operational use cases.
• Recommend and implement automation opportunities that improve data reliability, efficiency, and operational excellence.

Requirements

• Experience as a Data Engineer, Data Platform Engineer, Data Integration Engineer, or similar role supporting large-scale data environments.
• Strong experience building and supporting backend data pipelines using modern data engineering practices.
• Experience with data integration, transformation, cleansing, and consolidation across multiple data sources.
• Strong understanding of data governance, data quality, metadata management, and data lifecycle management.
• Experience establishing and documenting data lineage, data flows, and data dependencies.
• Proficiency with SQL and data modeling concepts in enterprise data environments.
• Experience with cloud-based data platforms, data warehouses, and data lake architectures.
• Knowledge of data security, access management, and governance principles.
• Strong analytical, troubleshooting, and problem-solving skills with attention to detail.
• Passion for creating high-quality, trusted, well-governed data products.

Preferred Qualifications

• Experience supporting AI, machine learning, or responsible AI governance programs.
• Familiarity with data catalog, metadata management, data lineage, or data observability platforms.
• Experience implementing enterprise data quality and monitoring frameworks.
• Experience within financial services, fintech, payments, banking, or other highly regulated industries.

Benefits

• Internal career growth opportunities
• Opportunities to innovate in fintech
• Inclusive and diverse team atmosphere
• Professional and personal development
• Resources to contribute to your community

Type of hire: Experienced (relevant combination of work and education).
Position type: Full time.