Executive Director, Data & AI Platforms Engineering

As part of the Information Technology (IT) organization, the Executive Director Data and AI Platforms Engineering will oversee a range of technology systems, including integration platforms, MLOps for AI/ML model operations, Gen AI platforms for advanced analytics, master data management systems, and enterprise reporting platforms, all aimed at enhancing data-driven decision-making across the enterprise. This role will collaborate with teams in R&D and Commercial for the development, deployment, and maintenance of cutting-edge data engineering solutions and AI technologies in collaboration.

Job Description

Key Responsibilities:

Leadership in Data Engineering and Integration Technologies:

• Direct and oversee the design, development, and maintenance of enterprise data engineering solutions and integration platforms, ensuring seamless data flow, interoperability, and scalable performance across IT systems and business functions.

MLOps and Gen AI Platforms:

• Lead the implementation and optimization of MLOps pipelines, ensuring the efficient deployment, monitoring, and maintenance of AI/ML models in production environments. Integrate Gen AI platforms to deliver AI-powered insights and decision-making capabilities, driving innovation across business operations. Collaborate with teams in IT and Data Analytics functions in R&D and Commercial to ensure that platforms support the use case needs while maintain the standards.

Master Data Management (MDM) and Data Engineering Platforms:

• Oversee the implementation and enhancement of MDM platforms to ensure the integrity, consistency, and governance of master data across the organization. Integrate these platforms with broader data engineering and architecture efforts, ensuring alignment with compliance and business objectives. Collaborate with other teams in the org that manage the data on these platforms.

Enterprise Reporting and Analytics:

• Manage the modernization and deployment of enterprise reporting platforms that provide real-time business intelligence and data visualization. Ensure these platforms are designed to support business stakeholders in monitoring performance, identifying risks, and making data-driven decisions, all supported by robust data engineering practices.

IT Infrastructure and Data Architecture:

• Collaborate with IT teams to create and maintain secure, scalable, and high-performance data engineering and architecture solutions. Ensure that the data platforms integrate with other advanced technologies, and cloud services, to support operational and business goals.

Innovation and Cross-Functional Integration:

• Explore and implement innovative data engineering solutions, including the integration of AI/ML platforms with enterprise systems (ERP, CRM, etc.). Lead the integration of diverse data platforms to ensure alignment with the company’s broader IT and business strategies.

Data Governance, Security, and Vendor Management:

• Collaborate with established data governance teams and assist in standing up data governance where gaps exist. Ensure compliance with data governance policies, security standards, and regulatory requirements across data engineering and integration platforms. Manage relationships with external vendors to ensure they meet internal security, compliance, and performance expectations.

Operational Efficiency and Excellence:

• Lead efforts in demand management, resource planning, and functional outsourcing to deliver high-quality data engineering and integration solutions efficiently and within budget. Drive continuous improvement in operational processes, ensuring alignment with business priorities while managing tech debt.

Strategic Planning and Execution:

• Develop and execute a strategic roadmap for data engineering, integration, and AI platforms, aligned with broader business and IT goals. Stay abreast of emerging technologies and lead the adoption of innovative tools and platforms that drive operational and business efficiency.

Qualifications/ Required

Knowledge/ Experience and Skills:

• Extensive leadership experience in IT, particularly in managing data engineering, enterprise integration platforms (e.g., Mulesoft), and data architecture.
• Strong expertise in MLOps, AI/ML platforms, and Gen AI systems, with a focus on utilizing advanced analytics for business transformation. Example of platforms include Mulesoft, Mattillion, Denato, DataIku, atacamma, Axway, Tableau etc.
• In-depth knowledge of master data management (MDM) systems and data engineering practices, ensuring consistency, quality, and governance across data platforms.
• Proven track rec