Associate Director, Data Quality Lead

About the role

Novartis is looking for an Associate Director, Data Quality Lead to build and advance enterprise data quality practices so that its most important data assets are accurate, reliable and fit for purpose. The role works across Data Governance, Data Engineering and Data Product teams and with business stakeholders, driving improvements in data trust and unlocking the value of data for analytics, innovation, regulatory excellence and AI. The preferred location is the East Hanover, New Jersey site, though remote work may be possible subject to restrictions; there is no relocation support and the company does not sponsor visas.

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 turn business needs into measurable data quality requirements.
• Embed data quality controls throughout the data product lifecycle and certification process.
• Lead monitoring, reporting and performance tracking for critical data assets.
• Drive issue triage, root cause analysis, escalation and resolution.
• Work with engineering teams to automate quality checks and data observability.
• Support AI-ready data initiatives with trusted, governed, high-quality datasets.
• Maintain documentation, remediation plans, operational trackers and control evidence, and foster a culture of accountability and continuous improvement.

Required profile

• 8+ years in data quality, including 3+ years leading teams in a regulated industry (pharma/life sciences strongly preferred).
• Strong understanding of data quality dimensions, profiling, validation, cleansing, root cause analysis and remediation.
• Knowledge of data governance frameworks, stewardship, critical data elements, metadata, lineage and data product certification.
• Understanding of data engineering concepts such as pipelines, ingestion, transformation, controls, monitoring and production support.
• Ability to define measurable quality rules and translate business requirements into technical ones.
• Knowledge of AI-ready data concepts such as trusted datasets, lineage, quality thresholds and governed usage.

Required skills

• Data quality tools, data observability platforms, SQL, data catalogs, workflow tools and reporting dashboards.
• Team leadership and stakeholder management.

What we offer

• Expected salary of $152,600 - $283,400 per year, with a performance-based cash incentive and possible eligibility for annual equity awards.
• US-based eligible employees receive health, life and disability benefits, a 401(k) with company contribution and match, and a time-off package including vacation, personal days and holidays.