Lead Data Engineer

The U.S. Pharmacopeial Convention (USP) USP is an independent scientific organization that collaborates with the world's top experts in health and science to develop quality standards for medicines, dietary supplements, and food ingredients. USP's fundamental belief that Equity = Excellence manifests in our core value of Passion for Quality through our more than 1,100 talented professionals across five global locations to deliver the mission to strengthen the supply of safe, quality medicines and supplements worldwide. 

The Digital product engineering team at USP is seeking a Data Engineer with expertise in building robust data pipelines, managing large-scale data infrastructure, and enabling advanced analytics capabilities.  This role is critical to supporting projects that align with our mission to protect patient safety and improve the health of people around the world.   We are looking for a professional who understands the value of clean, accessible, and well-organized data, and who enjoys designing systems that empower data scientists, analysts, and business stakeholders to derive actionable insights. The ideal candidate will be passionate about data architecture, cloud technologies, and scalable engineering solutions that drive innovation and impact.

• Design and implement scalable data collection, storage, and processing pipelines to support enterprise-wide data needs.
• Implement and maintain data governance frameworks and data quality checks within data pipelines to ensure compliance and reliability.
• Build and optimize data models and data marts to support self-service analytics and reporting tools such as Tableau, Looker, and Power BI
• Partner with data scientists to operationalize models by integrating them into production-grade pipelines, ensuring scalability, performance, and maintainability.
• Collaborate with cross-functional stakeholders (business, product, analytics, and engineering teams) to translate business requirements into scalable data solutions and prioritize data initiatives.
• Provide technical leadership and architectural guidance for data platform design, ensuring alignment with enterprise standards and long-term data strategy.
• Lead design reviews, code reviews, and data architecture discussions to ensure best practices, reusability, and high-quality deliverables.
• Collaborate with platform, DevOps, and security teams to ensure secure, cost-effective, and scalable data infrastructure.
• Influence data roadmap and strategy by identifying opportunities for data platform enhancement, automation, and cost optimization.

The successful candidate will have a demonstrated understanding of our mission, commitment to excellence through inclusive and equitable behaviors and practices, ability to quickly build credibility with stakeholders, along with the following competencies and experience:

• Experience with scientific chemistry nomenclature or prior work experience in life sciences, chemistry, or hard sciences or degree in sciences
• Experience with pharmaceutical datasets and nomenclature
• Experience in developing Machine learning & Deep learning models; Familiarity with MLOps and deploying ML models in production environments.

• Ability to explain complex technical issues to a non-technical audience