Join an onsite team in Jacksonville to help build governed, trustworthy data foundations that enable responsible AI.

Design, develop, and maintain scalable backend data pipelines, integrations, and data platforms for AI governance and analytics use cases.
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 downstream consumption.
Work with business, technology, and governance stakeholders to define data ownership, stewardship, and accountability models.
Implement data quality controls, monitoring frameworks, and observability practices to proactively identify and resolve data issues.
Create and maintain metadata management processes that improve discoverability, traceability, and governance compliance.
Support data access governance by helping define, automate, and monitor access controls and permissions.
Build and maintain data validation, reconciliation, and audit capabilities to strengthen trust in enterprise data assets.
Partner with AI, machine learning, and analytics teams to ensure governed data is available for model development and operational workflows.
Identify and implement automation opportunities to improve data reliability, efficiency, and operational excellence.

Experience as a Data Engineer, Data Platform Engineer, Data Integration Engineer, or similar role in 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.
Solid 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 delivering high-quality, trusted, and well-governed data products.

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 in financial services, fintech, payments, banking, or other highly regulated industries.

Data Engineer, AI Governance

Job Description