Manager, eQMS Technologies

The Manager, eQMS Technologies supports data-driven quality and compliance decisions by advancing analytics, AI-enabled insights, measurement solutions, and electronic quality management system capabilities across RDQA, R&D, and Enterprise Quality. This role partners with Quality, Business Technology Services, and process owners to translate business needs into requirements, improve data quality and accessibility, and deliver dashboards, metrics, and advanced analytics that support continuous improvement, global regulatory compliance, informed decision-making, and proactive risk management.
Support the development and execution of quality analytics and AI roadmaps aligned with RDQA, R&D, and Enterprise Quality priorities.
Build and maintain automated reporting, dashboards, KPI frameworks, and eQMS health metrics to monitor quality process performance and compliance.
Develop advanced analytics and AI capabilities, including trend, anomaly, and predictive risk signals, to identify quality and compliance risks earlier.
Partner with process owners and BTS to translate business needs into requirements, data products, and insight-driven actions.
Establish data definitions, quality controls, and governance for key quality datasets and metrics.
Enable self-service use of dashboards and insights through training, playbooks, and documentation.
Review and approve SLC documentation to support compliant use of data and models in regulated environments.
Support eQMS system ownership responsibilities, including system health monitoring, release/change coordination, issue escalation, user access/process support, and partnership with BTS and process owners to ensure systems remain fit-for-purpose, compliant, and aligned with business needs.
Required:
Bachelor’s Degree in Pharmacy, Engineering, Computer Science, Data/Analytics, Business, or relevant course of study
4–6 years of experience in quality systems, engineering, data/analytics, or business support in a regulated environment
Demonstrated experience developing metrics, dashboards, and analytical insights for process performance and compliance monitoring
Working knowledge of data fundamentals (data modeling, data quality, governance) and analytical methods (descriptive/inferential statistics, trend analysis)
Preferred:
Experience with BI and analytics tooling (e.g., Power BI or similar) and query languages (SQL); scripting/analysis in Python, R or similar is a plus
Experience applying machine learning/AI techniques to operational quality problems (e.g., risk prediction, signal detection, text analytics) and understanding of model lifecycle considerations (monitoring, bias, drift)
Experience implementing or enhancing computerized QA/eQMS solutions with a focus on data enablement and insights
Knowledge of tools and techniques that can be leveraged into actionable activities and influence decision making
Knowledge of Risk Management principles to help organization focus on the most impactful activities
Quality Systems knowledge and related experience
Travel: Yes, 10 % of the Time

Employment type
Full-time

Work arrangement
Hybrid