Associate Director, Data Quality Lead

Job Description Summary #LI-Onsite

Location:

East Hanover, New Jersey Novartis is unable to offer relocation support: please only apply if accessible.

Company will not sponsor visas for this position.

The preferred location for this role is East Hanover, New Jersey site but remote work may be possible (there may be some restrictions based on legal entity). Please note that this role would not provide relocation as a result. If associate is remote, all home office expenses and any travel/lodging to specific East Hanover, New Jersey site for periodic live meetings will be at the employee’s expense.

The expectation of working hours and travel (domestic and/or international) will be defined by the hiring manager.

Help shape the foundation of trusted, AI-ready data that powers critical business decisions across Novartis. As Associate Director, Data Quality, you will play a pivotal role in building and advancing enterprise data quality practices that ensure our most important data assets are accurate, reliable, and fit for purpose. Working across Data Governance, Data Engineering, Data Product teams, and business stakeholders, you will drive measurable improvements in data trust, lead enterprise-wide quality initiatives, and help unlock the full value of data for analytics, innovation, regulatory excellence, and artificial intelligence.

If you are passionate about data quality, operational excellence, and delivering meaningful impact at scale, this is an opportunity to help transform how data fuels the future of healthcare.

Job Description

Key Responsibilities 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.

Essential Requirements8+ years in data quality, including 3+ years leading teams in a regulated industry (pharma/life sciences 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.

The salary for this position is expected to range between $152,600 - $283,400 per year. The final salary offered is determined based on factors like, but not limited to, relevant skills and experience, and upon joining Novartis will be reviewed periodically. Novartis may change the published salary range based on company…