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1. 資訊設備管理維護(含軟硬體及網路) 2. 有程式語言撰寫經驗(C# , ASP , PHP ...)或有網管經驗者佳 3. 熟資料庫SQL語法
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【全球智慧製造】 你知道Garmin的智慧工廠嗎? 你知道火星上出現過Garmin的產品嗎? 你知道飛行員總是配戴Garmin的手錶上天空嗎? 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 如果你想體驗不同的文化,綻放自己的光芒! 現在就投遞履歷,讓我們見識你的獨特潛力! 【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】 -User Training and Support: Assist in preparing tutorials for data platform features, including basic operations and SQL queries. Provide basic technical support to users, helping resolve daily data access issues. -Documentation and Resource Management: Help draft and update user manuals and FAQs for the data platform. Support the organization and maintenance of internal knowledge resources. -Promotion Activities: Planning and executing promotional activities for the data platform (e.g., workshops, presentations). Facilitate cross-department communication to help users understand the value and applications of the data platform. 【Requirements】 -Basic Skills: Proficiency in SQL with knowledge of basic query syntax. Interest in learning BI tools (e.g., Tableau, Power BI). -Communication Skills: Strong verbal and written communication skills to convey technical concepts clearly. -Personal Traits: Quick learner of new tools and technologies with a proactive attitude toward problem-solving. Customer-focused mindset with a willingness to support and assist colleagues. -Preferred Qualifications: Familiarity with basic principles of database normalization. Preliminary experience in data modeling (e.g., Star Schema, Snowflake Schema). Experience in data analysis. Participation in technical support or internal training-related work.
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1.熟悉資料庫之SQL語法指令(PL/SQL或T-SQL)執行資料轉換及驗證。 2.撰寫ORACLE SQL、PLSQL及程式開發 3.資料查詢、檢查及修改 4.其他主管交辦事項
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【全球智慧製造】 你知道Garmin的智慧工廠嗎? 你知道火星上出現過Garmin的產品嗎? 你知道飛行員總是配戴Garmin的手錶上天空嗎? 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 如果你想體驗不同的文化,綻放自己的光芒! 現在就投遞履歷,讓我們見識你的獨特潛力! 【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】 -Design and Implement data streaming pipelines/ETL batch services on Hadoop and Spark eco-systems supporting production line -Design and implement scalable, high performance and low latency Web service/RESTful APIs. -Data warehouse dimensional modeling and developing and optimizing complex SQL queries for applications. -Cross-functional collaboration with domain experts and data scientists -Coach and mentor junior data engineers to be more effective individual contributors -Investigate the next generation data pipeline and architecture to improve data quality and integrity. 【Requirements】 -3 Years+ of programming using Scala/Java/Python -3 Years+ of experience in data modeling for both OLTP and OLAP databases on data warehouse, data lake, and enterprise big data platforms. -3 Years+ of hands on experience in developing Web service/Restful APIs -Experience with testing, data validation, and data quality assurance, performance tunning -Strong knowledge of ER modeling, big data, enterprise data, and physical data models -Willing to further discuss with data user to know their truly intention and requirement
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1.數據需求分析與開發測試驗證 2.Hadoop與Airflow平台管理 3.專案廠商管理與功能測試驗證 4.系統日常維運與問題處理
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1.熟悉資料庫之SQL語法指令(PL/SQL或T-SQL)執行資料轉換及驗證。 2.撰寫ORACLE SQL、PLSQL及程式開發 3.資料查詢、檢查及修改 4.其他主管交辦事項
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【全球智慧製造】 你知道Garmin的智慧工廠嗎? 你知道火星上出現過Garmin的產品嗎? 你知道飛行員總是配戴Garmin的手錶上天空嗎? 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 如果你想體驗不同的文化,綻放自己的光芒! 現在就投遞履歷,讓我們見識你的獨特潛力! 【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】 -Develop and Maintain data streaming pipelines/ETL batch services on Hadoop and Spark eco-systems supporting data analysis dashboard such as smart factory dashboard, war room...etc -Ingesting data from different sources to data middle office platform such as Kafka and HDFS/HIVE. -Data warehouse dimensional modeling and developing and optimizing complex SQL queries for applications. -Design and implement scalable, high performance and low latency Web service/RESTful APIs. -Cross-functional collaboration with domain experts(PE) and data scientists(DS) in Garmin 【Requirements】 -Experience in Git/SVN or other version control tools -Familar with at least one programming language like Scala/Java/Python -Experience in ER modeling/data modeling for both OLTP and OLAP databases on data warehouse, data lake, and enterprise big data platforms. -Strong interest in big data platform and related open source like Spark, Redis, Kafka, ELK -Willing to further discuss with data user to know their truly intention and requirement -Be positive, data loving and interested in growing into more senior data engineer
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【全球智慧製造】 你知道Garmin的智慧工廠嗎? 你知道火星上出現過Garmin的產品嗎? 你知道飛行員總是配戴Garmin的手錶上天空嗎? 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 如果你想體驗不同的文化,綻放自己的光芒! 現在就投遞履歷,讓我們見識你的獨特潛力! 【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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1. 配合數位產品發展目標,執行資料治理任務,參與數據工程相關專案(跨單位溝通)。 2. 分析業務需求,撰寫規格文件,提出報表開發流程解決方案。 3. 進行數據相關專案管理工作,包含溝通、需求訪談、定義需求規格等事項。 【履歷投遞】 **加快審核方式:下載制式履歷表進行填寫投遞(https://mma.tw/O05FY)
