IT Governance (Director, Data & AI Policy & Standards)
 Spectraforce Technologies | |
 United States, New Jersey, Newark | |
 Aug 13, 2026 | |
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Job Title :-IT Governance (Director, Data & AI Policy & Standards)
Duration :- 12 months contract to hire Location: Newark, NJ (Onsite 5 days/week) OR (3 days onsite/week) Role Description: As the Director, Data & AI Policy & Standards at Client, you will serve as a key operational and strategic leader responsible for shaping, maintaining, and operationalizing Clients enterprise data and AI governance "rulebook." You will own enterprise data and AI governance policies, standards, regulatory alignment, control requirements, and decision frameworks that ensure data and AI are governed, protected, and responsibly used across the company. In this role, you will translate enterprise governance strategy into clear, actionable policies and minimum standards that can be consistently applied across a global, federated organization. You will work closely with senior leaders, data domain owners, AI and technology teams, risk, compliance, and business partners across U.S. and international markets to drive alignment, clarity, and adoption of data and AI governance expectations. At its core, this role ensures that Client's data and AI governance direction is well defined, consistently interpreted, and embedded into how teams design, build, and operate data and AI solutions. You will help balance innovation with risk management, enabling trusted, ethical, and compliant use of data and AI throughout their lifecycle. What to Expect on a Typical Day * Own and maintain Client's enterprise data and AI governance policies, standards, control requirements, and minimum expectations, ensuring they remain current, clear, and actionable. * Maintain and evolve the enterprise data and AI governance "rulebook," including policies, standards, decision frameworks, and documented interpretations. * Define and steward enterprise data and AI standards that promote trust, quality, transparency, explainability, and responsible use across the organization. * Partner with data domain owners, data stewards, AI teams, technology leaders, and business stakeholders to ensure consistent interpretation and implementation of enterprise policies and standards. * Support a federated governance model by providing clear guidance and guardrails that enable local decision making while maintaining enterprise alignment and regulatory compliance. * Collaborate with Risk, Compliance, Legal, Privacy, and Model Risk partners to ensure data and AI governance policies align with regulatory obligations, internal risk frameworks, and supervisory expectations. * Incorporate Responsible AI principles into governance standards, including expectations related to transparency, fairness, explainability, accountability, and lifecycle oversight of AI use cases. * Guide the integration of data and AI governance requirements into product roadmaps, digital initiatives, data platforms, AI development practices, and Agile delivery processes. * Support the design and operation of enterprise governance decision forums, including intake criteria, escalation paths, and documented outcomes. * Partner with implementation and enablement teams to ensure policies and standards are translated into tooling, workflows, and operational practices. * Contribute to the deployment and adoption of enterprise data governance, data quality, and AI governance tooling by defining policy requirements and control expectations. * Develop and deliver education, awareness, and guidance materials that increase understanding of data and AI governance policies across technical and non technical audiences. * Promote consistent application of data and AI governance standards during solution design, development, deployment, and ongoing operations. * Monitor adoption and adherence to policies and standards through reporting, metrics, and issue analysis, and recommend adjustments as needed. * Provide expert guidance to leaders and governance forums on data and AI governance risks, tradeoffs, and policy implications. * Influence outcomes across the enterprise without direct authority by leveraging expertise, relationships, and well articulated governance principles. The Skills and Expertise You Bring * Bachelor's degree required; an advanced degree in Data Management, Information Systems, Computer Science, AI, Engineering, or a related field preferred (or equivalent experience). * Proven experience in data governance, data management, AI governance, data quality, privacy, or related disciplines. * Strong experience developing enterprise policies, standards, frameworks, or control requirements in regulated environments. * Working knowledge of Responsible AI concepts and how AI governance requirements are translated into practical standards and controls. * Experience partnering closely with Risk, Compliance, Legal, Privacy, and Technology teams to align governance with regulatory and policy expectations. * Strong analytical skills with the ability to translate complex requirements into clear, actionable standards and guidance. * Experience with data governance and data quality platforms such as Collibra, Informatica, Ataccama, BigID, Global IDs, or similar tools. * Familiarity with modern data architectures, cloud data platforms, and AI development environments (e.g., Snowflake, cloud ecosystems). * Excellent documentation skills, with proven ability to produce clear policies, standards, decision frameworks, and operating guidance. * Experience working in Agile or product oriented environments and embedding governance requirements into delivery practices. * Strong communication and facilitation skills, with the ability to explain complex concepts to diverse technical and business audiences. * Demonstrated ability to influence without authority and drive alignment across a global, federated organization. * Strategic, detail oriented, and execution focused mindset, with accountability for outcomes. * Comfort working across cultures, geographies, and regulatory environments. * A passion for building sustainable, clear, and trusted data and AI governance capabilities that support innovation and responsible growth. Preferred qualifications: * Certifications such as CDMP (Certified Data Management Professional) or Data Governance and Stewardship Professional (DGSP). * Experience in regulated industries (e.g., financial services, healthcare). * Familiarity with data privacy regulations and risk management practices. * Background in Agile methodologies, lean delivery and product-centric delivery models. | |