Role Overview
We are seeking a Data & AI Capability Lead to build and lead the Data & Artificial Intelligence capability within our Global Capability Center (GCC).
This leader will be responsible to deliver, scale, and operationalize data platforms, BI & AI solutions that enable AI-powered decision intelligence across global operations.
The Role Combines
- Strategic architecture thinking
- Hands-on technical leadership
- Team building and talent development
- Cross-functional stakeholder engagement
This is a high-impact leadership role supporting R&D, Operations, Finance and overall digital transformation initiatives.
Key Responsibilities
- Data & AI Strategy Execution
- Translate enterprise digital and AI strategy into a GCC delivery roadmap
- Build scalable data & AI
- Support AI-first initiatives including predictive maintenance, quality analytics, GenAI copilots
- AI lifecycle management (model governance, MLOps, observability)
- Platform Delivery
- Implementation and evolution of:
- Cloud-native data platforms (Databricks on AWS)
- Lakehouse architectures
- Real-time data pipelines
- GenAI integration frameworks (e.g., Bedrock-hosted LLM frameworks)
- Deliver secure integration with brownfield systems (MES, ERP, equipment data, OT systems)
- Drive modern data engineering practices (CI/CD, IaC, automated testing)
- BI & AI Solution Delivery
- Oversee delivery of:
- AI/ML models (Edge AI experience preferred)
- Anomaly detection and small signal detection models
- GenAI assistants for operations, maintenance, and IT
- Agentic AI workflows
- Institutionalize MLOps and scalable deployment patterns
- Ensure business value realization (cost savings, uptime improvement, yield
- Team Leadership & Capability Building
- Build and lead a high-performing Data & AI team (Data Engineers, ML Engineers, Data Scientists)
- Develop citizen AI enablement playbooks
- Establish strong engineering culture (code quality, experimentation, peer review)
- Mentor future technical leaders
- Governance, Risk & Compliance
- Ensure alignment with enterprise cybersecurity frameworks, responsible AI standards and governance models
- Manage data privacy, model explainability, and audit requirements
- Collaborate with IT Security and Enterprise Architecture
Required Qualifications
- Bachelor's or Master's degree in Computer Science, Data Science, Engineering, or related field
- 12–15+ years of experience in Data Engineering, AI/ML, or Advanced Analytics
- 10+ years in a leadership or team lead role
- Strong hands-on experience with:
- Cloud platforms (AWS preferred)
- Databricks / Lakehouse architectures
- Python / Spark
- MLOps practices
- Experience working in enterprise or manufacturing environments
Preferred Qualifications
- Experience in semiconductor or discrete manufacturing
- Exposure to OT/IT integration
- Experience with GenAI frameworks and LLM integration
- Familiarity with reinforcement learning or advanced optimization
- Experience working in global matrix organizations
Leadership Competencies
- Systems thinking in complex brownfield environments
- Strong execution discipline
- Builder mindset (from zero to scale)
- Data-driven decision making
- High ownership and accountability
- Ability to influence without authority
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