Position Summary
Cedar Gate Technologies, an IQVIA business, is hiring a Director of Data Quality to lead data quality strategies within a complex healthcare data environment, and to modernize data quality processes using Agentic AI and intelligent automation. While this may be an appealing career move for you, we will only consider candidates who can show significant data quality experience in data ecosystems beyond just QA engineering or software QA, and with experience designing and deploying AI agents and agentic workflows at an enterprise level.
In this role you will ensure healthcare data is accurate, complete, timely, and fit for operational, regulatory, and analytical use. You will provide leadership across data quality management, governance, reporting integrity, data stewardship, and process improvement. As Director you will partner closely with cross-functional leaders to ensure trusted data supports value-based outcomes, regulatory reporting, and strategic decision-making.
In addition, this role serves as a Subject Matter Expert in Agentic AI frameworks and AI-driven data quality capabilities, responsible for advancing the organization’s use of automation and AI to scale and modernize data quality operations.
Roles & Responsibilities
Data Quality Strategy & Leadership
- Develop and lead the enterprise-wide Data Quality strategy aligned to business goals and regulatory requirements
- Establish data quality standards, policies, and operating models
- Define and monitor key dimensions including accuracy, completeness, consistency, timeliness, and integrity
- Implement data quality scorecards, dashboards, and executive reporting
- Serve as the enterprise leader for data quality practices
AI Agents & Agentic Frameworks
- Serve as a Subject Matter Expert in Agentic AI frameworks and AI agents, leading the design and implementation of AI-enabled data quality capabilities across the enterprise, including data profiling, anomaly detection, validation, monitoring, root cause analysis, and automated issue triage and remediation recommendations
- Define and operationalize AI use cases within the Data Quality framework, ensuring alignment with business priorities, regulatory requirements, and enterprise risk standards
- Establish and enforce governance standards for AI-driven data quality processes, including human oversight, explainability, and auditability, ensuring responsible and compliant AI adoption
- Partner with Data Engineering, AI/ML, and Architecture teams to deploy scalable, production-grade AI-enabled data quality solutions across data platforms and pipelines
Data Quality Operations
- Lead teams responsible for identifying, prioritizing, and resolving data quality issues
- Establish repeatable processes for profiling, root cause analysis, and remediation tracking
- Embed data quality controls into data pipelines, platforms, and reporting environments
- Leverage automation and AI to reduce manual effort and improve efficiency
- Drive continuous improvement initiatives across data quality processes
Cross-Functional Collaboration
- Partner with leaders across Operations, Clinical, Compliance, IT, Analytics, and Product
- Translate business needs into data quality requirements and AI-driven solutions
- Drive alignment on data ownership, definitions, and governance practices
- Communicate complex data and AI concepts to executive and non-technical stakeholders
Team Leadership & Development
- Lead and develop a high-performing team across data quality, governance, and data operations
- Establish performance metrics, goals, and career development plans
- Build capabilities in AI-enabled data quality, automation, and modern data management practices
Job Location
Burlington, MA (Boston)
Work Arrangement
Hybrid (3 days in office, 2 remote)
Experience / Qualifications
- 10+ years of experience in data quality, data management, data governance, and data operations
- 5+ years of leadership experience managing teams or enterprise data initiatives
- Hands-on experience with AI agents, agentic frameworks, or AI-enabled automation
- Experience implementing agentic workflows or intelligent automation
- Demonstrated experience implementing data quality frameworks, controls, and monitoring capabilities
- Bachelor’s degree in relevant fields such as Data Management, Computer Science, Healthcare Administration, or Analytics. Master’s degree preferred
- Experience applying AI to data quality processes such as monitoring, anomaly detection, or remediation for enterprise data operations is highly preferred
- Experience working with data pipelines, data platforms, or analytics ecosystems
- Experience in healthcare payer, healthcare provider, or healthcare technology organizations is preferred
- Knowledge of healthcare standards (FHIR, HL7, HEDIS, ICD, etc.) will enhance your candidacy.
- Experience with data governance tools, data quality platforms, or data catalogs will help you be successful in the position.
- Familiarity with responsible AI practices and AI governance frameworks will reduce your learning curve
- To be eligible for this position, you must reside in the same country where the job is located.
The potential base pay range for this role, when annualized, is $110,200.00 - $307,200.00. The actual base pay offered may vary based on a number of factors including job-related qualifications such as knowledge, skills, education, and experience; location; and/or schedule (full or part-time). Dependent on the position offered, incentive plans, bonuses, and/or other forms of compensation may be offered, in addition to a range of health and welfare and/or other benefits.
