Chief Data Officer (CDO)

Title	Chief Data Officer (CDO)
Department	Data & Analytics / Executive Leadership
Reports to	[Chief Executive Officer / Chief Information Officer / Chief Operating Officer]
Location	[Remote / Hybrid / On-site]
Employment type	Full-time
Salary	[Salary range. Postings with a range perform significantly better, and several states require one.]

Position overview

The Chief Data Officer (CDO) provides executive leadership for [Company]'s enterprise data strategy, governance, and analytics. This role treats data as a strategic asset and sets the direction for how data is managed, protected, and used across the organization.

The CDO partners closely with executive leadership, technology, security, privacy, compliance, and business units to establish data governance, improve data quality, enable analytics and AI, and ensure data is used ethically and in line with regulatory requirements.

As organizations compete on the strength of their data and analytics, the CDO serves as the senior authority on data strategy, data governance, and the responsible use of data across the enterprise.

Key responsibilities

Data strategy

• Develop and execute the enterprise data strategy and roadmap.
• Position data as a strategic asset aligned with business objectives.
• Set priorities for data platforms, analytics, and AI enablement.
• Establish data operating models and organizational structures.
• Present the data agenda to executive leadership and the Board.

Data governance

Establish and lead the enterprise data governance program, including:

• Data ownership, stewardship, and accountability models
• Data policies, standards, and definitions
• Metadata management and data cataloging
• Master and reference data management

Data quality and management

• Set enterprise standards for data quality and integrity.
• Oversee data lifecycle, retention, and archival practices.
• Improve accuracy, completeness, and consistency of critical data.
• Maintain data quality metrics and reporting.

Analytics and value

Enable analytics, business intelligence, and AI use cases that create measurable value, including self-service analytics, decision support, and the responsible use of data in models and automation.

Privacy and compliance

Partner with privacy, legal, and compliance leaders to ensure data is collected, used, and protected in line with applicable regulations, including alignment with GDPR, CCPA, and the DAMA-DMBOK body of knowledge.

Data protection and risk

• Partner with security to protect enterprise data assets.
• Address data-related risk within enterprise risk management.
• Oversee data sharing, classification, and access controls.
• Support incident response for data quality and integrity issues.

Culture and enablement

Build enterprise data literacy and a culture of data-driven decision making, including training, communities of practice, and change management across business units.

Required qualifications

• Bachelor's degree in Data Science, Computer Science, Statistics, Information Systems, Business, or a related discipline. Master's degree preferred.
• 12 to 15+ years of progressive experience in data management, analytics, or information leadership.
• 5+ years leading enterprise data, governance, or analytics functions.
• Experience briefing executive leadership and Boards of Directors.
• Strong understanding of data governance, data quality, analytics, and privacy.
• Track record of building data programs in complex organizations.

Preferred certifications

One or more of: CDMP (DAMA), DGSP, CIPP, CIPM, CDPSE, or relevant cloud data platform certifications.

Technical knowledge

Enterprise data strategy, data governance, data quality, master and reference data management, metadata and data cataloging, data architecture, analytics and business intelligence, data privacy, data lifecycle management, cloud data platforms, and the responsible use of data in analytics and AI.

Essential competencies

Strategic leadership, executive communication, Board presentation skills, business alignment, change leadership, program management, ethical judgment, and negotiation and influence.

Success measures: first 12 months

• Establish or refresh the enterprise data strategy and roadmap.
• Stand up or mature the data governance program.
• Define data ownership, stewardship, and accountability.
• Baseline and improve quality of critical data domains.
• Enable priority analytics and AI use cases.
• Align data practices with privacy and regulatory requirements.
• Build executive and Board data reporting.
• Advance enterprise data literacy and culture.

About [Company]

[Two or three sentences about your organization, the maturity of your program, and what the first year looks like. Candidates in this field respond to honesty about whether they are joining a build or an established function.]