AI Project Manager/System Analyst (Data Science & AI Team)

【職位優勢】 

• 全球一線客戶協作：負責北美 Tier 1 客戶之關鍵產品開發，主導全球資料中心運算節點的研發。 

• 尖端硬體開發實務：領導機架式伺服器NPI 專案，累積國際化專案管理與領導RD團隊經驗。 

【工作內容】 

1. 端到端專案管理：主導從 RFQ 提案、NPI 開發至量產階段的專案管理。 

2. 專案規劃：確立專案範疇、預算編列、樣品需求評估，並運用 MS Project 建立專案時程與 NUDD 風險預判。 

3. 領導核心團隊：協調跨部門 Core Team（硬體、軟體、機構、測試、安規、工廠），確保設計開發、打樣測試及認證計畫如期達成。 

4. 國際客戶專案聯繫：作為客戶RD團隊之主要溝通窗口，主持專案週會、達成客戶需求並落實 JDM/ODM 合作模式。 

5. 風險控管與應變處理：針對專案異常（如：關鍵電子料件缺料、測試異常、生產瓶頸）快速啟動應變機制，引導相關部門進行 Root Cause 分析和解決方案。 

6. 管理樣品生產計劃：與工廠PM合作規劃 PCBA、機構件、系統組裝之備料策略與生產製程，確保 NPI 試產與順利銜接量產。 

7. 量產後生命週期維護 (Sustaining)：負責規劃和執行替代料驗證、設計變更及量產階段之技術支援。

1. 競爭市場分析評估與規劃 

2. 專案規劃與執行

1.負責RPA機器人產品專案的管理、配置、實施工作，參與產品功能設計及開發； 

2.負責完成RPA產品的現場POC測試工作，與客戶的溝通交流等； 

3.完成與工作相關的技術文檔編寫、技術培訓等工作 

4.主管交辦事項

1.SAP 系統維護以及外掛程式開發 

2.處理用戶需求 

3.SAP 專案導入 

4.主管交辦事項

＜About the job＞  

As the Senior Data Engineer or Data Architect, you‘ll join the various advanced Data Science & AI Projects in the corporate headquarters. As well as developing intelligent applications via related AI and Big Data Analytics Technology for digital transformation, you will have plenty of opportunities to develop emerging applications based on different use cases and expand your tech skillset in this world-class company (Fortune Global 500, 20th). 

＜Job Description＞ 

*Type 1：Senior Data Engineer 

Responsible for acquiring data using API, Web scraping, or other data accessing protocol/scripting and developing the ETL data pipelines, and the data aggregation systems. Using software development experience to design and build high-performance automated systems. As below: 

1. Data Processing 

(1)Data ETL(Extracting/Transforming/Loading) process engineering and querying from relational data management(such as SQL Script). 

(2)Building systematic data quality processes and checks to ensure data quality and accuracy. 

(3)Solid coding experience in Python or Java. 

2. Data Pipeline Development 

(1)Develops a data integration process, including creating scalable data pipelines and building out data services/data APIs. 

(2)Create a data processing automation and monitoring mechanism by optimizing the data pipeline process.  

(3)Experience with dataflow/workflow/management tools, such as Apache Nifi, Apache Airflow, Azkaban, etc., is preferred. 

3. Data Crawling 

(1)Build scalable tools that automate web crawling, scraping, and data aggregation from various web pages using frameworks such as Scrapy. 

(2)Accessing data from REST APIs, particularly in parsing data in disparate formats such as JSON and XML, and developing automated engineering.  

(3) (Nice to Have) Knowledge of server-based front-end/UI technologies, including Vue/React and HTML/CSS, is preferred. 

*Type 2：Data Architect 

Responsible for designing, implementing, and maintaining scalable and reusable system architectures/data architectures for complex data structures and large data in data science and AI projects. As below: 

1. Data Schema Design 

(1)Collaborate with the team to design DB/Table Schema and Data Schema. 

(2)Consolidate the requirements and use data engineering tech to design and implement a robust Data Mart.  

(3)Experience handling all kinds of structured/semi-structured/unstructured data and streaming data is preferred. 

(4)Hands-on experience with Dimensional Data Modeling(Column-based data warehouse) or NoSQL Schema design. 

2. Data Platform Architecture 

(1)Design and build data infrastructure/platform components to support complex data pipelines ingesting various data from multiple internal and external data sources and processing. 

(2)Familiar with Big Data frameworks and processing technologies, ex: Hadoop, Apache Spark, NoSQL ...etc. 

(3)Familiar with AZURE or AWS cloud data services(hands-on experience with cloud infrastructure will be a plus) 

(4)Familiarity with the Linux OS environment, the Shell Scripting, and infrastructure knowledge.  

(5)(Nice to Have)Experience with declarative infrastructure/container technologies, such as Docker and Kubernetes (k8s/k3s). (Nice to Have).