Senior Manager, Data & AI Governance Architecture

Sony Corporation of America located in New York NY is the U.S. headquarters of Sony Group Corporation based in Tokyo Japan. Sonys principal U.S. businesses include Sony Electronics Inc. Sony Interactive Entertainment LLC Sony Music Entertainment Sony Music Publishing and Sony Pictures Entertainment Inc. With some 900 million Sony devices in hands and homes worldwide today a vast array of Sony movies television shows and music and the PlayStation Network Sony creates and delivers more entertainment experiences to more people than anyone else on earth. To learn more: SUMMARY

The Senior Manager of Data & AI Governance Architecture is a key leader within Sony HQs Digital Transformation (DX) division operating as part of the Data Enablement function a group chartered to advance Sonys digital transformation by creating the discipline trust and accountability that make responsible data use scalable and sustainable.

This roleconsolidatesand architecturally formalizes governance expectations across various governance domains including privacy engineering metadata and classification access governance platform architecture data quality and AI governance translating them into enterprise standards reusable design patterns and policy-as-code requirements embedded in platforms and workflows.

The Senior Manager partners with Platform Engineering Systems Architecture Legal/Privacy Information Security Product PMO and AI teams along with Sony operating companies (OpCos) and business data producers to design next-generation data and AI governance architectures and ensure adoption. This is a senior high-impact role shaping Sonys global data and AI landscape.

1. Architect the Enterprise Data & AI Governance Framework

• Design the unified data & AI governance architecture integrating privacy metadata access lineage DQ security and AI governance.

• Translate legal privacy security and AI risks into operational control requirements aligned to enterprise data flow patterns.

• Define reusable architecture patterns and guardrails for compliant data and AI product development.

2. Develop Enterprise Standards Guardrails & Lifecycle Controls

• Create enterprise rules and standards for data classification access control AI model data usage quality expectations lineage and lifecycle transitions.

• Build lifecycle-aligned controls from data ingestion to deletion.

• Drive adoption of standards across DX.

3. Define Governance Ownership Models & Decision Paths

• Define who is accountable for key governance decisions byestablishingsimple who decides what guidance soOpCos product teams and reviewers know how decisions flow.

4. Operationalize Enterprise Governance Processes

• Work closely with the Operational Governance & Integration team to ensure governance blueprints become implemented and repeatable.

5.Establishand Report on Governance Maturity

• Define maturity and success metrics; build clear scorecards to track progress.