VP, Global Product Data

Datasite is where deals are made. We provide the data rooms and SaaS technology used in M&A and other high-value transactions, to deliver projects in more than 170 countries. Carrying that success into the future is all about you. Your useful skills, your unusual experience, your unique ideas. Everyone here brings something unexpected. What’s yours? Invest your talents in us, and we’ll return the compliment.

Job Description:

Datasite is seeking a visionary Vice President of Global Product Data Architecture & Engineering to lead the design, implementation, and adoption of modern data systems that power our suite of SaaS and DaaS products across multiple business units. This executive will oversee the creation of robust, scalable, and secure data architectures to support product innovation, data compliance, customer insights, and AI/analytics initiatives at enterprise scale.

As a cross-functional leader, the VP will partner closely with Product, Engineering, Security, Compliance, and Global Data Management teams to drive enterprise data strategy, ensure regulatory alignment, and enable the next generation of data-driven products and experiences.

Key Responsibilities

Data Architecture & Platform Leadership

• Define and execute a unified product data architecture vision across all SaaS platforms and BUs.

• Build high-performance, cloud-native data platforms supporting real-time analytics, machine learning, AI, data licensing, and scalable integrations.

• Develop and maintain enterprise-wide data models, ontologies, APIs, and pipelines that ensure consistency and reusability.

Data Engineering & Product Enablement

• Lead global teams responsible for data ingestion, transformation, cataloging, and storage pipelines.

• Collaborate with Product and Engineering teams to embed data capabilities into product roadmaps.

• Enable data-as-a-product thinking, ensuring high data quality, accuracy, observability, and operational reliability.

Governance, Compliance & Security

• Collaborate closely with the Data Management Office (DMO) to define and implement global data governance policies, standards, and processes.

• Translate enterprise data governance goals into actionable architectural frameworks and roadmaps.

• Evolve and enforce policies for data privacy, residency, lineage, and classification, ensuring adherence to global standards (e.g., GDPR, CCPA, HIPAA, SOC 2).

• Partner with Security and Compliance to implement data access controls, encryption, and audit frameworks.

• Collaborate with Legal and Risk to support due diligence, regulatory audits, and M&A integration.

Strategy, Innovation & AI Enablement

• Contribute to the enterprise data strategy and roadmap, aligning AI/ML and licensing initiatives with business outcomes.

• Evaluate and deploy emerging technologies in data architecture, automation, and self-service tooling.

• Support product monetization strategies through data productization and insights generation.

Leadership & Organizational Development

• Enhance and scale a global team of architects, engineers, and data product leaders.

• Champion a modern data culture focused on enablement, collaboration, and operational excellence.

• Foster cross-BU alignment and platform governance through strategic influence and executive partnership.

Qualifications

• 15+ years of experience in data architecture, engineering, or related fields within complex, multi-product organizations.

• Proven success leading data platform and architecture strategy in a SaaS/DaaS or technology-driven business.

• Strong expertise in modern data stack technologies (e.g., Snowflake, Databricks, Kafka, dbt, Airflow, cloud-native platforms).

• Deep understanding of data privacy laws, compliance frameworks, and data security principles.

• Experience navigating matrixed global environments, working across Product, Engineering, and Compliance stakeholders.

• Exceptional leadership, communication, and executive influencing skills.

Preferred Qualifications

• Advanced degree in Computer Science, Data Engineering, or related field.

• Background in product-oriented data management or data monetization.

• Experience supporting AI/ML and analytics use cases acros