Data & AI Governance Officer

Vantage Bank•Fort Worth, TX

About The Position

At Vantage Bank, we're driven by a deep commitment to supporting our customers, valuing our employees, embracing diversity, fostering meaningful connections, and providing outstanding service every step of the way. JOB SUMMARY The Data & AI Governance Officer is responsible for shaping, implementing, and championing the organization’s AI and data governance strategy across all platforms. They will act as a technical authority and mentor, driving responsible AI adoption, robust data governance, and operational excellence. The Data & AI Governance Officer will lead Data Engineering, Data Analytics, and partner with cross-functional teams. They ensure a compliant and effective deployment of AI and advanced analytics solutions, while fostering innovation and measurable business value through modern data platforms (e.g., Databricks, Python, cloud data lakes).

Requirements

Bachelor’s degree in Data Science, Computer Science, Engineering, Information Technology, or a related technical field, Masters/PhD preferred.
10+ years of experience in data governance, AI/ML delivery, or risk management.
5+ years of experience in a technical leadership role.
Proven leadership and mentoring of cross-functional teams; excellent communication and stakeholder engagement
Expertise in Databricks, Python, cloud data lakes (Delta Lake, Azure, AWS S3); skilled in R, SQL, MLOps tools (MLflow, Kubeflow, SageMaker, Azure ML)
Strong experience in AI/ML lifecycle, responsible AI, deploying solutions on Databricks
Knowledge of regulatory compliance (PCI, GLBA,GDPR), agile methodologies, DevOps, CI/CD, infrastructure-as-code
Experience in data visualization (Sigma, Tableau, Power BI, Looker, Qlik)
Experience with pipeline orchestration (Airflow, Azure Data Factory, AWS Glue)
Familiar with Scrum, Kanban, SAFe, and product management frameworks
Excellent organizational and prioritization skills, with the ability to balance multiple issues and projects in a fast-paced environment.
Excellent verbal, written, and interpersonal communication skills.
Must be self-motivated with strong initiative, high level of accountability, and attention to detail.
Must be a self-starter with the ability to work independently and as part of a team.
Ability to always maintain a high degree of ethical standards and complete confidentiality.

Nice To Haves

Financial services, digital banking transformation or Fintech experience.
Working in the Data, Enterprise Architecture, or Risk Management Office.
Digital assets, blockchain, cryptocurrency, DeFi governance expertise.
Strong grasp of banking products, operations, and value chains.
Advanced Databricks, Python, SQL, and cloud data engineering proficiency.
Experience operationalizing AI/ML in banking or digital asset contexts.
Proven change management and continuous improvement in technical settings.
Open banking, API ecosystems, and data sharing frameworks understanding.
Cloud migration, data center consolidation, platform modernization experience.
Credit, market, operational risk, or compliance analytics knowledge.
Hands-on use of metadata management tools (e.g., Atlan, Collibra), data cataloging, data quality platforms.
Data monetization or data-as-a-product implementation.
Relevant certifications (e.g., CDMP, CIPP, CAIE, DASCA, Microsoft Azure Data Engineer Associate).

Responsibilities

Directs cross-functional teams to establish AI principles focused on fairness, transparency, and explainability, while addressing governance and regulatory issues and promoting accountability and innovation across the organization.
Develops and executes enterprise data and AI governance strategies aligned with business goals, evolving regulations (OCC, FDIC, Federal Reserve, CFPB), and industry standards.
Establishes and leads data governance and AI committees to drive cross-functional collaboration and accountability.
Defines strategic roadmaps for data governance maturity, integrating emerging technologies and regulatory changes.
Integrates data governance with enterprise architecture and modernization efforts, while ensuring comprehensive AI governance throughout the model lifecycle including development, validation, deployment, monitoring, and decommissioning.
Represent the organization in industry, regulatory, and peer forums related to data governance and AI.
Designs, implements, and enhances governance frameworks, policies, and standards consistent with DAMA-DMBOK, DCAM, and banking regulations.
Implements unified data classification and ownership models to ensure accountability, and enforces privacy, security, retention, and quality policies that comply with GDPR, CCPA, and relevant regulations.
Partners with Information Security for incident response for data breaches, model failures, and AI ethics issues.
Builds partnerships with leadership, business units, Technology, Risk, Compliance, Legal, HR, and Audit.
Partners with Risk and Compliance to establish risk assessments for data governance and AI/ML platforms, addressing compliance gaps.
Supports regulatory examinations, audits, and assessments for data governance and model risk.
Implements and enforces data quality standards through automated monitoring, remediation, and comprehensive metadata management for lineage, glossaries, and cataloging.
Collaborates with Data Engineering to embed quality controls in pipelines and analytics.
Supports data-driven decision making while maintaining governance controls.
Influences technology architecture and investment decisions impacting data governance.
Recruits, mentors, and develops a high-performing team of governance, ethics, and compliance professionals.
Establishes clear roles, responsibilities, and development paths for governance team members.
Promotes knowledge sharing, best practices, and cross-training across the organization.
Other duties as assigned.