Associate Director, Data Quality Lead

• Define and advance enterprise data quality standards, frameworks, policies, and measurement practices
• Establish scalable quality rules, thresholds, scorecards, dashboards, and reusable control frameworks
• Partner with stakeholders to translate business needs into measurable data quality requirements
• Embed data quality controls throughout the data product lifecycle and certification process
• Lead enterprise monitoring, reporting, and performance tracking for critical data assets
• Drive data quality issue triage, root cause analysis, escalation, and resolution activities
• Collaborate with engineering teams to automate quality checks and data observability capabilities
• Support AI-ready data initiatives by ensuring trusted, governed, and high-quality datasets
• Maintain documentation, remediation plans, operational trackers, and control evidence
• Foster a culture of accountability, continuous improvement, and confidence in enterprise data

• 8+ years in data quality
• 3+ years leading teams in a regulated industry
• Pharma/life sciences experience strongly preferred
• Strong understanding of data quality dimensions, data profiling, data validation, data cleansing, root cause analysis, and remediation
• Knowledge of data governance frameworks, data stewardship, critical data elements, metadata, lineage, and data product certification
• Familiarity with data quality tools, data observability platforms, SQL, data catalogs, workflow tools, and reporting dashboards
• Understanding of data engineering concepts, including data pipelines, ingestion, transformation, controls, monitoring, and production support
• Ability to define measurable data quality rules and translate business requirements into technical requirements
• Knowledge of AI-ready data concepts, including trusted datasets, lineage, quality thresholds, and governed usage
• Must be accessible to the East Hanover, New Jersey site if applying for the preferred location
• Company will not sponsor visas for this position

Demonstrates expertise in defining and advancing enterprise data quality standards and frameworks, with a strong focus on data governance, quality measurement, and automation of quality checks. Proven ability to lead teams in regulated industries, particularly in pharma/life sciences, while fostering a culture of continuous improvement and accountability.

• Data Quality Management
• Data Governance Frameworks
• Root Cause Analysis
• Data Quality Tools
• Data Engineering Concepts

• Data Quality Dimensions
• Data Profiling
• Data Validation
• Data Cleansing
• Data Stewardship
• Metadata Management
• Data Lineage
• Data Product Certification
• Measurable Data Quality Rules
• AI-Ready Data Concepts

• Collaboration
• Continuous Improvement
• Accountability

• Pharma
• Life Sciences
• Regulated Industry
• Data Product Lifecycle
• Data Quality Issue Triage

• SQL
• Data Quality Tools
• Data Observability Platforms
• Data Catalogs
• Workflow Tools
• Reporting Dashboards