Head Data & Analytics

As the Head of Data & Analytics at a global manufacturing organization, you will play a crucial role in leading the enterprise data, analytics, and AI transformation. Your responsibilities will include defining and executing the data and AI strategy, establishing a Data & AI Center of Excellence, and driving adoption of cloud, generative AI, and agentic automation across key business functions such as manufacturing, quality, supply chain, finance, and R&D. Key Responsibilities: - Define and lead the enterprise data & AI roadmap aligned with digital transformation goals. - Build and manage cloud data platforms (Azure / GCP / AWS) with scalable, compliant architectures. - Oversee data engineering, governance, and master data management across ERP (SAP), MES, LIMS, and CRM ecosystems. - Drive analytics and GenAI adoption enabling conversational insights, contextual summarization, and intelligent automation. - Lead AI/ML initiatives in forecasting, process optimization, predictive quality, and reliability. - Ensure compliance with GxP, 21 CFR Part 11, and data integrity standards across all data and AI systems. Profile Requirements: - 10-15 years of experience in Data Engineering, AI/ML, or Analytics leadership, ideally in pharma, life sciences, or manufacturing. - Proven experience building and scaling cloud-based data platforms (Azure, AWS, or GCP). - Expertise in ETL/ELT, data lakes, MDM, and advanced analytics platforms (Power BI, Tableau, Looker, SAP Analytics Cloud). - Experience deploying GenAI and agentic AI models in enterprise or regulated environments. - Strong leadership, stakeholder management, and strategic thinking capabilities. - Bachelors or Masters in Computer Science / Data Science; MBA preferred. Joining this role will provide you with: - Opportunity to build a next-generation enterprise data and AI ecosystem from the ground up. - Collaboration with global business and technology leaders driving digital transformation. - Work at the intersection of AI innovation, compliance, and scalable data architecture.,