Managing Director, Data Management

The Managing Director, Data Management leads Plymouth Rock’s enterprise data governance process to ensure data is trusted, secure, well-classified, and accessible through Business Intelligence, Machine Learning, and AI applications.

 

This role will establish the policies, tools, and processes required to manage data as a strategic asset while supporting the company’s transition to an AI/ML-driven operating model.

 

Partnering closely with Data Product & Engineering, Data Services and business leaders, this role ensures that data is compliant, reusable, and that governance frameworks enable speed, innovation, and value delivery.

 

Key Responsibilities:

1. Enterprise Data Management Strategy

• Define and implement a comprehensive data management framework aligned to Plymouth Rock’s AI/ML-first data strategy.
• Establish enterprise standards for data classification, lineage, quality, retention, and access, ensuring data is managed as a controlled and auditable asset.
• Develop governance policies that support scalable consumption across Business Intelligence and AI/ML use cases.
• Promote a culture where data is treated as a strategic asset and company resource, with clear accountability for its quality and use.

1. Data Classification, Tagging, and Lineage

• Implement metadata management and data catalog capabilities that provide transparency into data origin, transformation, and usage.
• Ensure that all data products are properly classified, documented, and discoverable across the enterprise.
• Establish and enforce lineage tracking to enable traceability from source systems through downstream consumption.

1. Access Control, Security, and Responsible Data Use

• Define and enforce policies governing data access, consumption, and distribution across all platforms, including data warehouses, data lakes, and AI data services.
• Ensure governance frameworks support responsible AI usage, including controls around data privacy, bias, and regulatory compliance.
• Partner with Legal, Compliance, and Risk teams to maintain adherence to all applicable regulatory requirements.

1. Governance Enablement Across Data Services

• Establish governance processes and controls tailored to the three primary data consumption patterns:

• Business Intelligence
• Machine Learning
• AI / Agentic systems

• Ensure that governance standards are consistently applied across all environments while managing to the differing curation and consumption demands of data lake and data warehouse architectures.
• Enable secure and scalable data access for AI and ML systems without introducing bottlenecks to development or deployment speed.

1. Third-Party Data Acquisition and Management

• Lead the enterprise capability for sourcing, contracting, and integrating third-party data.
• Establish standards for evaluating, onboarding, and governing external data sources to ensure quality, compliance, and reusability.
• Manage relationships with key data vendors (e.g., LexisNexis, TransUnion, and others), ensuring contractual enforcement and effective data utilization.

1. Organizational Alignment and Accountability

• Work closely with data product owners and business data stewards to embed governance into day-to-day operations.
• Establish clear accountability for data quality, classification, and usage at the data product level.
• Support cross-functional execution by ensuring governance frameworks enable coordinated delivery across business, data, and AI teams.
• Drive transparency into data quality and governance performance through measurable KPIs.

Qualifications

 

Education

• Bachelor’s degree in Data Science, Computer Science, Information Systems or a related field required.
• Advanced degree preferred.

Experience Preferred

• 7+ years of experience in data governance, data architecture, or enterprise data management.