• Minimum 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 Qualifications 

• Expertise 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 Skills 

• Visionary 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.