Data Engineers

FIS; Florida; On-site; USD 90,000 - 120,000; Full time

Job summary

Fidelity Information Services, LLC is seeking a Data Engineer, AI Governance to build and maintain data foundations for responsible, trusted AI across the enterprise. You will ensure data is discoverable, traceable, reliable, and fit for purpose while enabling data lineage and ownership visibility.

You will collaborate with AI/ML teams and governance partners to ensure data is available for model development and production use, while driving quality and governance controls across data assets.

Qualifications

• Experience as a Data Engineer or similar in large-scale data environments.
• Strong backend data pipelines and data integration experience.
• Proficiency with SQL and data modeling.
• Understanding of data governance, data quality, metadata management, and data lifecycle management.
• Experience establishing and documenting data lineage, data flows, and data dependencies.

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, enabling visibility into where data originates, how it is transformed, and how it is consumed.
• Partner with business, technology, and governance teams to define data ownership, stewardship, and accountability models.
• Implement data quality controls, monitoring frameworks, and observability practices to proactively identify and resolve data issues.
• Develop metadata management processes that improve data 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 that improve trust in enterprise data assets.
• Collaborate 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.

Skills

Backend pipelines

SQL

Data governance

Data lineage

Cloud platforms

Data quality

Data security

Metadata management

Data integration

Troubleshooting

Tools

Data Catalog

Job description

Job Description

The future of money is being built right now. At FIS, we help the world's businesses, banks and communities move, manage and grow money with confidence. Join a team that values fresh thinking, works together to solve complex challenges, and creates technology that powers everyday life.

About the role

As a Data Engineer, AI Governance , you will design, build, and maintain the data foundations that support responsible, trusted, and scalable AI across FIS. This role combines deep backend engineering expertise with a passion for data quality, governance, and transparency. You will serve as a data wrangler and problem solver, ensuring data is discoverable, traceable, reliable, and fit for purpose while providing visibility into data lineage, ownership, and usage throughout the enterprise.

Your key 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, enabling visibility into where data originates, how it is transformed, and how it is consumed.
• Partner with business, technology, and governance teams to define data ownership, stewardship, and accountability models.
• Implement data quality controls, monitoring frameworks, and observability practices to proactively identify and resolve data issues.
• Develop metadata management processes that improve data 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 that improve trust in enterprise data assets.
• Collaborate 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.

What you bring

Required qualifications

• 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 exceptional attention to detail.
• Passion for creating high-quality, trusted, and 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 highly regulated industries.

The impact you'll make

As a Data Engineer, AI Governance , you will help establish confidence in the data that powers AI and business decision‑making across FIS. Your work will enable clear visibility into data origins, transformations, ownership, and consumption while ensuring high standards of quality, accessibility, and governance. By building trusted data foundations, you will play a critical role in advancing responsible AI adoption and delivering scalable solutions that create long‑term value for the organization.

What we offer you

Bring your ideas. Build your future. At FIS, you'll find the support, resources and opportunities to develop your career while helping shape the future of financial technology.

We offer:

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

Privacy Statement

FIS is committed to protecting the privacy and security of all personal information that we process in order to provide services to our clients. For specific information on how FIS protects personal information online, please see the Online Privacy Notice.

EEOC Statement

FIS is an equal opportunity employer. We evaluate qualified applicants without regard to race, color, religion, sex, sexual orientation, gender identity, marital status, genetic information, national origin, disability, veteran status, and other protected characteristics. The EEO is the Law poster is available here supplement document available here

For positions located in the US, the following conditions apply. If you are made a conditional offer of employment, you will be required to undergo a drug test. ADA Disclaimer: In developing this job description care was taken to include all competencies needed to successfully perform in this position. However, for Americans with Disabilities Act (ADA) purposes, the essential functions of the job may or may not have been described for purposes of ADA reasonable accommodation. All reasonable accommodation requests will be reviewed and evaluated on a case-by-case basis.