Hyundai GLOVIS America Inc. is looking to enable logistics automation through software-driven intelligence powered by enterprise-wide Data Lake architecture. This role will design and maintain data architecture, lead data standardization, integration, and utilization for AI training, operational analytics, and intelligent system deployment, while managing project execution and communication between headquarters and regional subsidiaries.
Requirements
- Familiarity with data analytics tools and techniques for monitoring system performance and supporting data-informed decisions required
- Knowledge of AI-ready data lifecycle and transformation required
- Proficiency in using AI tools, data processing platforms, and enterprise IT systems to support intelligent automation and analytics rquired
- Understanding of emerging IT trends and enterprise system architecture required
- Design, validate, and maintain scalable Data Lake architecture capable of collecting and integrating structured and unstructured data across enterprise systems (ERP, MES, WMS, TMS, WCS, etc.)
- Establish policies for data ingestion, standardization, cleansing, enrichment, and classification—including structured and unstructured data
- Design unified meta-data models and taxonomy rules to support efficient data discovery, lineage, and governance
Responsibilities
- Lead the design and planning of data integration between key logistics systems (e.g., WMS, WCS, TMS), enabling seamless automation across physical operations
- Identify and validate AI/ML technologies applicable to logistics and manufacturing, and translate them into data-driven operational models
- Define system interaction frameworks that support autonomous material flow, automated work instruction generation, and real-time process feedback
- Plan and oversee Proof-of-Concept (PoC) projects to validate new automation concepts before scaled deployment across operating sites
- Design, validate, and maintain scalable Data Lake architecture capable of collecting and integrating structured and unstructured data across enterprise systems (ERP, MES, WMS, TMS, WCS, etc.)
- Establish policies for data ingestion, standardization, cleansing, enrichment, and classification—including structured and unstructured data
- Analyze operational data to identify inefficiencies, process risks, and performance gaps using quantitative models and visualization tools
Other
- Serve as a primary coordination point between HQ and regional entities, ensuring clear communication of directives and structured feedback on execution progress
- Manage the execution of ongoing projects by tracking progress, managing dependencies, validating milestones, and compiling annual status reports
- Align project-level direction with broader corporate IT strategies to ensure consistency and strategic coherence
- Prepare structured documentation including meeting notes, issue logs, internal guides, and progress updates
- Good written and verbal communication skills in English and Korean: must be able to clearly document and convey ideas, processes, and requirements across teams preferred
