協助客戶對數據系統進行技術評估，並設計數據驅動的企業路徑為宗旨。透過數據轉型創建技術、安全無虞的架構與設計藍圖，結合現代數據技術和雲端服務，展現數據價值。在這份工作你會接觸地端數據工程與雲端數據工程，著重於零售數據系統之穩定性。歡迎追求系統優化、效能精進有興趣之人才，與我們攜手打造貼近客戶運用之數據服務。
【工作內容】
1. 熟悉資料倉儲與數據湖概念，進行數據清洗、資料整備等相關數據轉換與整合。
2. 熟悉數據工程的ETL流程，處理數據開發、自動化、測試、監控、佈署等相關技術解決方案。
3. 維運和規劃大數據處理系統，以確保日常數據的運作品質之傳輸性、高效性和準確性。
4. 與infra團隊合作，檢視數據存儲和數據架構的設計和維護，以確保數據的安全性和可擴展性。
5. 與零售數據專家領域緊密合作，以確保數據分析的準確性和可靠度。
6. 數據系統囊括雲端與地端技術。
7. 其他主管交辦事項。
【經驗需求】
1. 具備兩年以上數據系統開發與維運管理經驗。
2. 具備兩年以上使用Python和數據庫管理（SQL和no-SQL）的經驗。
3. 具備大數據系統維運和機器學習工具（Scikit-learn、Pandas）的經驗。
4. 具備數據倉庫的設計和實踐經驗，如 SSIS、Analyzer、Redshift、BigQuery 等。
【技能需求】
1. 熟悉SQL/PostgreSQL/Stored Procedure使用與撰寫經驗。
2. 熟悉Python程式開發經驗。
3. 熟悉數據排程、處理、清洗、製作報表的實務經驗。
4. 熟習常用的 Open Source 工具實務經驗。
5. 擅長解決問題、除錯、故障排除，提出問題解決方案。
Assist clients in conducting technical assessments of data systems and design data-driven enterprise solutions. Create secure and modern architectures and design blueprints by leveraging data transformation and integrating modern data technologies and cloud services to unlock the value of data. In this role, you will work on both on-premises and cloud data engineering, with a focus on the stability of retail data systems. We welcome individuals who are passionate about system optimization and performance improvement, and who are interested in collaborating with us to build data services that align closely with customer needs.
【Job Description】This position is part of the Data Center Team.
1. Familiarity with data warehousing and data lake concepts for data cleaning, data preparation, and related data transformation and integration.
2. Familiarity with ETL (Extract, Transform, Load) processes in data engineering, covering data development, automation, testing, monitoring, deployment, and related technical solutions.
3. Maintenance and planning of big data processing systems to ensure the quality of daily data transmission, efficiency, and accuracy.
4. Collaboration with the infrastructure team to review data storage and data architecture design and maintenance to ensure data security and scalability.
5. Close collaboration with retail data experts to ensure the accuracy and reliability of data analysis.
6. Involvement in both on-premises and cloud technologies for data systems.
7. Other tasks assigned by the management.
【Experience】
1. Minimum of two years of experience in data system development and maintenance.
2. Minimum of two years of experience using Python and database management (SQL and NoSQL).
3. Experience in big data system maintenance and machine learning tools (Scikit-learn, Pandas).
4. Experience in data warehouse design and implementation, such as SSIS, Analyzer, Redshift, BigQuery, etc.
【Skills】
1. Proficiency in SQL/PostgreSQL/Stored Procedure usage and writing.
2. Proficiency in Python programming.
3. Practical experience in data scheduling, processing, cleaning, and report generation.
4. Proficiency in using common open-source tools with practical experience.
5. Strong problem-solving, debugging, and troubleshooting skills with the ability to propose solutions.
