Design and implement a unified data development platform to improve the efficiency of global data producers, including intelligent IDE capabilities, workflow management, and multi-engine integration.
Define and own the company-wide architecture for AI and data infrastructure, spanning data acquisition, storage, processing, applications, and AI services across on-premise and cloud.
Collaborate with cross-functional teams to design, develop, and implement AI features, focusing on areas like natural language processing, data analysis, and predictive modeling.
Development of a sales planning and analytics platform for a premium German OEM in the Asia region, enabling data-driven business decisions through scalable data processing, integration, and API-based data consumption.
Possess at least a bachelor’s degree in related fields such as fluid mechanics, machine learning, civil and environmental engineering, coastal, ocean engineering.
Architecture for multiple plants. Design shared capabilities, facility configuration, access boundaries and data isolation. Establish a practical path from a few plants to many plants, using representative workloads and operational needs to guide decisions. Make each additional plant easier to onboard without creating separate code forks.
The Data Business Analyst and AI Engineer will bridge business requirements, enterprise data and AI-enabled delivery. The role will work directly with business users and technology teams to understand reporting and operational needs, analyze complex datasets, define functional and data requirements, and deliver reliable analytical and AI solutions.
Architecture for multiple plants. Design shared capabilities, facility configuration, access boundaries and data isolation. Establish a practical path from a few plants to many plants, using representative workloads and operational needs to guide decisions. Make each additional plant easier to onboard without creating separate code forks.
Rack, stack and install servers, network and storage equipment according to business requirements, including rail mounting, power connection and structured cabling (copper and fibre) with proper labelling
Design and develop internal flagship data analytics systems, applications and APIs that allow engineers and analysts to retrieve, triage and analyse information more efficiently
Rack, stack and install servers, network and storage equipment according to business requirements, including rail mounting, power connection and structured cabling (copper and fibre) with proper labelling
Lead and manage electrical commissioning and testing activities for data centers, ensuring compliance with project specifications and industry standards.
Design and implement a unified data development platform to improve the efficiency of global data producers, including intelligent IDE capabilities, workflow management, and multi-engine integration.