Manager, Data Governance & Knowledge Management

Apple•Cupertino, CA

About The Position

We are seeking a Manager of Data Governance & Knowledge Management to design, implement, and operate Finance’s data governance, data quality, and knowledge management capabilities. This role sits at the intersection of Finance, data engineering, and AI enablement, with a strong focus on execution and delivery. As part of the Finance Transformation organization, this role is responsible for ensuring Finance data and institutional knowledge are trusted, discoverable, explainable, and AI-ready. The manager will lead a small, dedicated team of engineers and partner closely with Finance Product, Engineering, IS&T, and Finance domain experts. This is not a policy-only governance role. It is a hands-on leadership role focused on building the foundations that allow analytics, automation, and AI to scale safely and effectively within Finance. DESCRIPTION This role ensures Finance can safely and confidently scale analytics and AI by building the data and knowledge foundations that make intelligence explainable, auditable, and trusted. It is a critical enabler of Finance Transformation and a key pillar of responsible AI adoption. In this role, success means: - Finance data is trusted, measurable, and consistently governed. - Finance knowledge (rules, policies, KPIs, controls) is structured and reusable, not locked in documents or tribal knowledge. - AI, analytics, and automation initiatives launch faster and with higher confidence because data and knowledge foundations are in place. - Finance users trust AI outputs because they are explainable and correctable. - Tangible progress is made toward AI readiness through delivered capabilities—not just frameworks.

Requirements

8+ years of experience in data governance, data management, analytics engineering, or related roles
2+ years proven experience managing, developing and coaching as leader of a team
Bachelors of Science (BS) or equivalent degree in Finance, Business Management, Computer Science, Engineering or a field required.

Nice To Haves

Experience implementing data quality frameworks, metadata management, lineage, and data catalogs.
Hands-on experience or strong exposure to semantic modeling, ontologies, or knowledge graphs.
Familiarity with AI/ML data requirements, including explainability, RAG, and human-in-the-loop feedback.
Experience working with modern data platforms (e.g., Snowflake, Dataiku, cloud-native stacks).
Strong ability to translate technical concepts into Finance and business context.
Experience with knowledge graph or semantic technologies (tool-agnostic).
Exposure to AI/ML governance or model input management.
Experience supporting audits, compliance, or SOX-related data processes.
Execution-oriented leadership with strong attention to detail
Ability to balance technical depth with business understanding
Strong collaboration and stakeholder management skills
Problem-solving mindset with a bias toward automation and scalability
Clear written and verbal communication across technical and non-technical audiences
Experience working in Finance or regulated environments