Career Category Information SystemsJob DescriptionMinimum 8 years of hands-on experience with PI Data Historian (OSIsoft/AVEVA), batch reporting, and analytics solution architecture, deployment, and lifecycle management in a GMP-regulated pharmaceutical, biotechnology, or manufacturing environment.Extensive experience with advanced analytics platforms and reporting (Spotfire, Tableau, Power BI) and integration with PI and manufacturing data sources.Proven track record leading global, multi-site manufacturing data transformation programs, including direct management and mentorship of technical teams.Deep understanding of GxP regulations, CSV/validation, and SDLC best practices for manufacturing data systems.Demonstrated expertise with IT/OT cybersecurity, data integrity, cloud-based architectures, and modern data platforms (Databricks, data lakes, data fabrics, containerization, streaming analytics).Strong software development experience, with proficiency in Python, SQL, or other relevant programming/scripting languages for data engineering and analytics automation.Solid knowledge of AI/ML concepts and their application to manufacturing analytics (predictive analytics, anomaly detection, root cause analysis, etc.).Excellent financial and vendor management experience.Outstanding communication, relationship-building, and stakeholder engagement skills at all levels, including executive leadership.Preferred QualificationsExpertise in advanced OSIsoft PI/AVEVA historian modules (e.g., PI Asset Framework, PI Vision, PI Batch, PI Event Frames, PI Integrator for Business Analytics).Experience deploying data integration solutions between PI, SAP, MES, and automation platforms (Rockwell, DeltaV, OPC UA, Pi connectors/Interfaces, etc.).Proficiency with cloud-based analytics, Databricks, data lakes, and/or data fabric architectures for large-scale manufacturing data enablement.Professional certifications in Data Analytics, PI System, or Project Management (e.g., CAP, PMP, or equivalent).Experience representing manufacturing data programs with regulatory agencies and external partners.Familiarity with modern software development practices, DevOps, containerization (Kubernetes), and data science toolkits.Soft SkillsVisionary leadership with a passion for nurturing technical talent and high-performing analytics teams.Strategic thinking, adaptability, and a growth mindset for leveraging data and analytics in manufacturing.Exceptional organizational, analytical, and complex problem-solving abilities.Resilience in a dynamic, fast-paced, and global environment.Commitment to diversity, inclusion, and fostering a collaborative data-centric culture..
