面議(經常性薪資達4萬元或以上) 新北市新店區 3年工作經驗 2天前更新
【全球智慧製造】
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全球智慧製造服務計畫(GSMS)透過AI、機構、電控、資料科學、IoT、大數據等技術,將智慧製造系統,即時控制與調整全球生產系統,且在地化支援亞洲、美洲、歐洲多個國家
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【Introduction】
With increasing velocities, varieties and complexity of data at Process Integration (PI), the PI Data Engineering Team becomes the important role supporting existed or new projects using big data techniques to manipulate large streaming/batch dataset with various format on highly efficient way.
【Responsibilities】
-Strategic Promotion and Planning:
Lead the promotion of the data platform, develop cross-departmental collaboration strategies, and ensure effective adoption.
Design advanced training programs tailored to different levels of users.
-Technical Support and Problem Solving:
Provide advanced technical support to users, resolving complex issues related to BI tool integration, data queries, or system operations.
Assist in optimizing the data platform based on user feedback and requirements.
-Requirements Analysis and Feedback:
Gather requirements from various departments, analyze usage scenarios, and provide actionable feedback to the technical team.
Help design and test new features to enhance the data platform‘s user experience.
-Guidance and Team Management:
Mentor junior team members, share expertise, and help improve the overall team skillset.
Drive team goals and ensure project milestones are met.
【Requirements】
-Technical Expertise:
Proficiency in SQL with experience in database architecture and optimization.
Expertise in at least one BI tool (e.g., Tableau, Power BI) with advanced applications.
Deep understanding of data platform or data lake architecture.
-Experience Requirements:
3–5 years of relevant experience (e.g., data analysis, data engineering, system support).
Prior participation in or leadership of large-scale data projects is preferred.
-Communication and Leadership Skills:
Exceptional cross-departmental communication and coordination skills to drive project progress effectively.
Experience in training or mentoring users and team members at various levels.
-Personal Traits:
Detail-oriented and capable of managing multiple tasks with creativity and initiative in problem-solving.
Sensitive to user needs and quick to respond to and fulfill business requirements.
-Preferred Qualifications:
Expertise in database normalization principles and practices.
Experience in data modeling, with knowledge of design techniques (e.g., Star Schema, Snowflake Schema).
Familiarity with data platform-related technologies (e.g., Dremio, Databricks) or data governance processes.
Background in data engineering or software development.
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