[Hiring] Director of Data Trust @Children's Hospital of Philadelphia

Role Description

Director of Data Trust will lead data governance providing both strategic and operational leadership across the enterprise data warehouse, business intelligence (BI) ecosystem, and analytical products, ensuring that data is reliable, secure, well‑understood, and responsibly used. As a leader within the Data & Analytics organization and reporting to the AVP of Data Science, this role oversees the Data Trust Office and drives the evolution of data governance capabilities that support clinical, research, operational, and enterprise reporting needs, as well as emerging AI‑enabled solutions.

The Director is responsible for establishing, executing, and advancing CHOP's data governance strategy which includes developing and refining the frameworks, policies, and standards that strengthen data quality, transparency, security, compliance, and ethical use.

While the role is anchored within the Data & Analytics organization, the Director will partner closely with clinical, operational, and technical leaders to improve data quality and stewardship at upstream source systems that feed the enterprise data warehouse. These partnerships are essential to ensuring downstream reliability for reporting, analytics, predictive modeling, and AI.

As CHOP expands its use of advanced analytics, predictive modeling, and AI, the Director of Data Trust will build and scale the governance foundation required for trustworthy insights, positioning the organization for future growth and maturity in enterprise data governance.

What you will do

• Operational oversight of the Data Trust Office activities in support of clinical and operational analytic leaders:
• Define and execute a multi-year Data Trust and Data Governance roadmap aligned to organizational strategy, clinical and operational priorities, research needs, and AI initiatives.
• Integrate data governance into broader Data & Analytics, digital, and AI strategies, ensuring governance efforts are sequenced, scalable, and outcome driven.
• Ensure governance standards are consistently applied throughout the data asset lifecycle, including acquisition, integration, validation, use, maintenance, and archival.
• Provide thought leadership on modern governance practices that balance innovation with risk management and regulatory compliance.
• Promote enterprise-wide adoption of repeatable governance standards rather than one-off solutions.
• Data Quality, Metadata & Transparency:
• Scale and mature the Data Quality Center of Excellence (COE), including profiling, monitoring, root-cause analysis, prioritization, and remediation of data quality issues, imperative for trusted analytics and AI solutions.
• Establish enterprise standards for data quality, metadata, lineage, and documentation that enable data consumers to understand, trust, and appropriately use data.
• Define data quality metrics and KPIs and report progress to executive stakeholders.
• Oversee adoption and optimization of the enterprise data catalog and metadata management processes, ensuring discoverability and usability across domains.
• Access, Privacy, Security & Responsible Data Use:
• Align data governance practices with enterprise and/or regulatory privacy and security standards.
• Refine and mature data access controls, balancing usability with protection of sensitive data.
• Enforce data classification schemas and corresponding access controls to ensure data is securely managed and aligned with privacy, security, and compliance standards.
• Ensure responsible data use and ethical considerations are embedded into analytics and AI initiatives.
• Partner with enterprise AI governance efforts to ensure data readiness, documentation, and guardrails support responsible AI adoption.
• Governance Operations & Policy Management:
• Develop, publish, and maintain enterprise data governance policies, standards, and procedures.
• Establish and support data stewardship roles and accountability frameworks across clinical, research, and operational domains.
• Translate governance decisions into actionable standards, priorities, and execution plans across the data ecosystem.
• Leverage automation and scalable workflows to improve governance efficiency and consistency.
• Collaboration, Councils & Change Management:
• Lead Data Trust council, stewardship forums, and working groups, ensuring alignment, accountability, and follow-through.
• Integrate into and serve as a trusted advisor to executive leaders and enterprise committees/councils by framing options, clarifying trade-offs, and assessing impacts.
• Partner closely with Clinical, Informatics, Research, Digital Technology Services, Analytics, Finance, HR, and Operations leaders to embed governance into day-to-day practices as relevant.
• Drive change management and communication strategies to support adoption of new standards, definitions, and governance processes.
• Team & Operational Leadership:
• Build, lead, and develop a high-performing Data Trust Office team.
• Provide coaching, clear expectations, and professional development opportunities.
• Manage operational responsibilities including resource planning, prioritization, budgeting input, succession planning and performance measurement.
• Foster a culture of collaboration, accountability, transparency, and customer focus.
• Strategic Alignment & Continuous Improvement:
• Monitor healthcare, analytics, and AI trends to continuously evolve governance practices.
• Proactively adapt Data Trust capabilities to support emerging data sources, technologies, and use cases.
• Partner with Data Literacy and Enablement programs to embed Data Trust concepts into enterprise training and education.
• Champion strategic programs like Master Data Management (MDM) to support enterprise data alignment, streamline cross system integration, and strengthen the overall data governance ecosystem.

Qualifications

• Bachelor's Degree in Data science, informatics, computer science, biostatistics, healthcare, business administration, or a related field - Required
• Master's Degree in related discipline - Preferred

Requirements

• At least ten (10) years in healthcare, life sciences, or biomedical environments - Required
• At least five (5) years leading or managing enterprise data governance or data management initiatives - Required
• At least two (2) years demonstrated experience maturing data governance capabilities in complex, regulated organizations - Required
• At least two (2) years experience supporting advanced analytics and AI use cases in healthcare - Required

Skills and Abilities

• Strong knowledge of data governance, data quality, metadata management, and master data management practices (Required proficiency)
• Understanding of healthcare data privacy, security, and regulatory requirements (Required proficiency)
• Experience with business intelligence and analytics platforms (e.g., Power BI, Tableau, Qlik, Business Objects) (Required proficiency)
• Familiarity with data requirements for AI, machine learning, and predictive analytics (Required proficiency)
• Experience with data catalogs, lineage, and governance tooling (Required proficiency)
• Knowledge of modern data platforms, cloud environments, and DataOps practices (Required proficiency)
• Proven ability to lead complex initiatives through influence and collaboration (Required proficiency)
• Excellent communication, facilitation, and data storytelling skills (Required proficiency)
• Ability to operate effectively in ambiguity and adapt to evolving priorities (Required proficiency)
• Experience with Epic analytics tools (Caboodle, Radar, SlicerDicer, Reporting Workbench) a plus (Preferred proficiency)
• Familiarity with Python, R, Snowflake, GitHub, CI/CD, and automation a plus (Preferred proficiency)

Benefits

• Salary Range: $100,000.00 - $375,000.00 Annually
• This job is eligible for an incentive program.
• Factors such as skills and experience could result in an offer above the salary range noted in this job posting.