BI/Data Platform Senior Engineer - 內湖_JR202505011

[職務概述] 研華的數據中台已具一定規模，正邁向下一階段的效能優化與架構升級。邀請你加入一個數據驅動的團隊，參與核心資料平台的建置與優化，並有機會： 深入大型資料流架構，解決高效能、穩定性的挑戰。 自主挖掘現有系統的改進空間，提出並實作優化方案。 與跨部門緊密合作，確保數據服務能支撐多元業務場景。 我們期待一位細心、主動、有推進力的工程師，不僅完成交付，也能驅動團隊持續前進。 [必備條件] 3-5 年資料工程或相關經驗。 熟悉資料流架構設計，具備 ETL / ELT 開發經驗。 熟練資料 API 串接設計與實作，有第三方 API 整合經驗。 熟悉資料庫技術（SQL / NoSQL），具備資料庫效能調校及維運經驗。 具備 Python 或 .NET Core的實作經驗，作為主要開發工具。 良好的專案管理與溝通能力，能主動推動專案並與多方協作。 [加分項目] 有分散式架構經驗（如 Kafka、Spark、Kubernetes 等）及其應用經驗。 具備資料安全、權限控管經驗。 有實務雲端資料平台經驗（如 AWS, Azure, GCP）。 有數據治理、資料血緣、品質管理經驗。 曾負責/主導中大型資料專案，具備「從 0 到 1」或「持續優化」的推動能力。 [Summary] Advantech data platform has already reached a significant scale and is now moving toward the next phase of performance optimization and architectural enhancement. You will join a data-driven team to participate in the construction and optimization of our core data platform, with opportunities to: Dive deep into large-scale data architectures to tackle challenges in performance and stability. Proactively identify areas for improvement within existing systems, propose, and implement optimization solutions. Collaborate closely with cross-functional teams to ensure data services effectively support diverse business needs. We are looking for an engineer who is detail-oriented, proactive, and capable of driving projects forward—someone who not only delivers but also pushes the team to continuously improve. [Requirements] 3-5 years of experience in data engineering or related fields. Familiar with data pipeline architecture design; experience in ETL/ELT development. Proficient in designing and implementing data API integrations, including third-party API integrations. Solid experience with database technologies (SQL / NoSQL), including performance tuning and maintenance. Hands-on experience with Python or .NET Core as primary development tools. Strong project management and communication skills, with the ability to independently lead projects and collaborate across teams. [Nice to Have] Experience with distributed architectures (e.g., Kafka, Spark, Kubernetes) and their practical applications. Knowledge of data security and access control. Practical experience with cloud-based data platforms (e.g., AWS, Azure, GCP). Experience in data governance, lineage, and quality management. Proven track record in leading or being a key contributor to medium-to-large-scale data projects, with the ability to drive initiatives from the ground up or continuously enhance existing systems.