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公司介紹 我們的客戶是一家長期深耕金融科技與數位創新的大型金融機構，近年積極投入資料平台與雲端架構升級，打造企業級數據基礎設施，支援數據分析、AI模型與多元金融場景。 團隊目前正推動 Modern Data Stack 與資料治理體系建設，導入雲端數據平台、資料血緣管理與自動化資料流程，讓數據能真正驅動產品決策與金融服務創新。 對資料工程師而言，這是一個能接觸 大規模資料、成熟商業場景與完整數據治理架構 的環境，能在穩定產業背景下，參與企業級資料平台的設計與落地。 工作內容 設計與維護 雲地混合（Hybrid Cloud）數據架構 建立與開發 大規模 Data Pipeline，處理結構化、半結構化與非結構化資料 建立資料處理流程的 自動化監控與維運機制 評估與導入 Modern Data Stack，提升資料治理、品質與血緣管理能力 使用資料治理與元資料管理工具，管理企業數據資產 維護與優化 Airflow 工作流程平台，支援資料科學與分析團隊的資料處理流程 設計部署與監控策略，確保資料平台穩定與高可用性 使用的技術 Python SQL Apache Airflow GCP（Composer / Dataflow） Terraform CI/CD Pipeline Data Governance / Data Lineage Modern Data Stack

About the Role We are seeking a Systems Engineering Architect to lead the design, implementation, and operational excellence of our large-scale distributed systems infrastructure. This role is critical in driving architectural decisions and ensuring reliability, scalability, and performance across our platform. You will work cross-functionally with product engineering, DevOps, SRE, and support teams to evolve the foundational systems that power our data pipeline, RDBMS solutions, container-based microservices, and cloud-native deployments. Key Responsibilities ● Architect and design large-scale distributed systems across major cloud service providers (AWS, Azure, GCP). ● Drive the strategy and execution of data infrastructure leveraging Postgres, Elasticsearch/ELK, Snowflake, and Databricks. ● Design and scale distributed data ingestion systems using Kafka or RedPanda. ● Lead the integration of CI/CD systems and automation pipelines. ● Guide the implementation and evolution of containerized microservices on Kubernetes across Linux and Windows environments. ● Own production infrastructure scalability, resiliency, and high availability strategies. ● Implement and optimize observability solutions, including logging, monitoring, and metrics systems. ● Conduct deep performance tuning and capacity planning across application and database tiers. ● Lead incident escalation, conduct root cause analysis (RCA), and drive continuous improvement for production reliability. ● Collaborate with internal stakeholders to balance architecture excellence with pragmatic delivery timelines. Required Qualifications ● 3+ years of experience in systems engineering, with at least 5 years in an architectural or technical leadership role. ● Proven experience designing and operating systems at cloud-scale across AWS, Azure, or GCP. ● Deep expertise in large-scale RDBMS (Postgres preferred) and Elastic Stack (ELK), with working knowledge of Snowflake and Databricks. ● Hands-on experience building and managing data streaming pipelines using Kafka or RedPanda. ● Proficiency in container orchestration using Kubernetes, and managing microservices at scale. ● Strong background in both Linux and Windows systems engineering. ● Track record of leading production-grade CI/CD and deployment automation strategies. ● Deep understanding of monitoring, metrics, and alerting systems (e.g., Prometheus, Grafana, Datadog). ● Exceptional debugging, performance tuning, and troubleshooting skills in large-scale environments. ● Demonstrated experience with RCA and handling critical production escalations under pressure. Preferred Qualifications ● Experience in security-conscious or regulated environments (e.g., financial services, healthcare, government). ● Familiarity with Infrastructure as Code (IaC) tools like Terraform, Pulumi, or CloudFormation. ● Contributions to open-source infrastructure or systems projects.

About the Role We are looking for a UI/UX Full Stack Engineer with a passion for creating powerful, intuitive, and data-rich enterprise applications tailored for the process industries—including energy, manufacturing, and industrial automation. In collaboration with data scientists, product managers, and domain experts, you will design and build the next generation of intelligent user experiences that enable complex data exploration, graph-based interaction, and persona-aware workflows. Inspired by platforms from C3.ai, Aveva, AspenTech, Palantir, and Siemens, your work will bring industrial AI and analytics to life for operators, engineers, and executives across multi-tiered organizations. Key Responsibilities ● Design and implement enterprise-grade full-stack applications that blend data analytics, BI, and AI insights into seamless user experiences. ● Lead UI/UX design and development for user-defined dashboards, adaptive workflows, and domain-specific visualizations. ● Build multi-layered persona-driven interfaces that adapt to organizational roles—from plant operators to corporate executives. ● Develop graph-based interaction models and visual tools that enable exploration of connected data, such as equipment hierarchies, supply chains, or asset relationships. ● Integrate with data pipelines, APIs, and backend systems to surface real-time industrial data and machine learning outputs. ● Translate complex analytical results into intuitive and actionable visual elements (e.g., alerts, KPIs, scenario simulators). ● Ensure high usability and performance of applications across devices and environments, especially in operational settings. ● Collaborate with stakeholders to validate use cases, iterate on designs, and drive feature adoption. ● Maintain engineering quality through testing, CI/CD integration, and agile collaboration. Required Qualifications ● 6+ years of experience in full-stack or front-end engineering with strong UI/UX sensitivity. ● Proven track record delivering modern enterprise applications with a focus on analytics, decision support, or industrial workflows. ● Expertise in React, TypeScript, modern JavaScript, and visualization libraries (e.g., D3.js, Plotly, ECharts). ● Backend experience with Node.js, Python (FastAPI or Flask), or Java, and integration with REST/GraphQL APIs. ● Familiarity with graph-based UI patterns and libraries (e.g., Cytoscape.js, Sigma.js, Neo4j visual tooling). ● Experience integrating with BI and AI systems, including dashboard frameworks, ML outputs, and embedded analytics. ● Understanding of user-centered design, accessibility, and responsive design principles. ● Knowledge of data handling (structured, semi-structured) and API integration for time-series, events, or industrial telemetry. ● Excellent communication skills and a strong ability to bridge the gap between engineering, design, and domain experts. Preferred Qualifications ● Prior experience in the process industries, industrial automation, or manufacturing systems. ● Familiarity with multi-tenant, role-based applications supporting enterprise hierarchies. ● Exposure to design systems and frameworks like Material UI, Ant Design, or custom component libraries. ● Understanding of security, auditability, and scalability in enterprise software environments. ● Experience with deployment on cloud-native platforms (AWS, Azure, GCP) and containerized environments (Kubernetes, Docker).

❗️投遞履歷請一律至專屬的職缺網頁：https://25sprout.teamdoor.io/s/ML8ElGFS 目前此職缺為常態徵才，直接透過 Cake平台投遞將不會回覆唷 我們正在尋找一位 Mid-level SRE（Site Reliability Engineer），成為團隊的可靠後盾。你的任務是確保系統穩定運行、雲端環境高效管理、流程持續自動化，讓用戶體驗更順暢、工程師開發更專注。如果你熱愛新技術，喜歡動手解決問題，也樂於與不同角色協作，歡迎加入我們一起：） ▍你的工作將包括： Linux 作業系統管理與維運（RedHat / Debian / Ubuntu 等）網站/應用環境建置與維護（LAMP / LNMP）CI/CD 流程整合與最佳化（Jenkins / GitLab CI/CD）憑證、金鑰與機密管理（SSL/TLS、Vault 等）雲端平台資源管理（AWS EC2 / S3 / RDS、Azure、GCP 等）建置監控與告警系統，確保服務高可用性（Prometheus / Grafana / ELK）自動化工具與基礎架構即程式碼導入（Terraform / Ansible / CloudFormation）

Please apply via the JKOPAY website; we will primarily review resumes submitted through this platform.【THE ROLE THE TEAM】 As the Data Team Lead at JKOPay, you will take on a leadership role in managing and mentoring the Data Engineering team. You will be responsible for overseeing the design, development, and maintenance of JKOPay’s data systems, including both real-time and batch processing. With JKOPay handling over 3 billion transactions monthly for more than 6 million users in Taiwan, your leadership will be crucial in ensuring data accuracy, scalability, and efficiency. A significant aspect of this role involves infrastructure planning and development. You will lead the team in architecting and optimizing data infrastructures to ensure scalability, high availability, and performance across multiple platforms and environments. Collaborating closely with cross-functional teams, you will guide the implementation of infrastructure solutions that support the rapid growth of JKOPay’s business and evolving data needs. This is a strategic position that will allow you to shape the future of JKOPay's data infrastructure while supporting the growth of the team and organization. 【WHY YOU SHOULD BE INTERESTED】 Lead and mentor a team of data engineers in building and maintaining scalable ETL pipelines, ensuring data integrity and security.Drive infrastructure planning and design for data platforms to ensure performance, scalability, and reliability.Collaborate with business and engineering teams to define data requirements, design data models, and drive the development of data products.Lead efforts in optimizing data systems for performance, scalability, and cost-efficiency across multiple environments, including cloud (GCP) and on-premises data centers.Oversee the entire lifecycle of data projects, from conception to deployment, ensuring timely and high-quality delivery.Take ownership of the continuous improvement of JKOPay’s data infrastructure and engineering practices to meet the needs of a rapidly growing business.Provide technical guidance on the adoption of new technologies and data platforms to drive innovation in the team.

亞洲據點最多的 Google Cloud 經銷夥伴，我們自 2016 年成立於日本，致力於協助企業導入與優化雲端架構。您將扮演關鍵的售前技術角色，串聯客戶需求與雲端解決方案，推動企業成功邁向雲端轉型。此職位將結合技術深度與顧問能力，從需求訪談、架構設計到方案導入，全面參與客戶的雲端轉型歷程。 【職務內容】 負責 Google Cloud 與 Google Workspace 產品之技術推廣與售前支援，涵蓋需求訪談、解決方案架構設計、技術簡報與產品 Demo，協助業務團隊提升提案品質與成交機率，加速客戶決策流程擔任 Google Cloud 售前技術工程師（Pre-Sales Solution Engineer），負責與客戶進行需求訪談與技術諮詢根據客戶業務場景與系統架構，設計並規劃 Google Cloud 雲端解決方案，包含架構設計與環境建置參與專案導入過程，提供技術支援並協助客戶順利完成雲端部署深入分析客戶既有系統痛點，進行技術評估並提出具體的優化與轉型建議持續研究 Google Cloud 相關技術與解決方案，並透過技術文章與公開分享（研討會 / Workshop）推廣實務經驗結合產業趨勢與雲端服務，提供具可行性與效益導向的架構優化建議

【Responsibilities】Collaborating with the engineering team to ensure seamless CI/CD workflows.Maintaining uptime for operational components, including managing multiple Kubernetes clusters with varying hardware configurations.Overseeing the management of global infrastructure.Opti

【公司介紹】 我們是一家深耕台灣市場、擁有數百萬活躍用戶的金融科技平台，長期專注於打造整合支付與嵌入式金融服務的數位生態圈。產品服務橫跨線上與線下場景，並持續拓展跨境合作與創新金融應用。 在高速成長與龐大交易量的環境下，數據已成為公司最核心的資產之一。團隊正啟動數據中台與基礎架構升級計畫，期望建立更高擴展性與高可用性的數據平台，支撐未來數年業務成長。 此職位將直屬技術最高主管，參與數據架構與技術策略規劃，能見度高、決策影響力強，對於希望從「工程執行者」邁向「技術與組織塑造者」的數據主管而言，是難得的舞台。 【工作內容】 帶領並培養 Data Engineering 團隊，建立高效且高品質的工程文化 規劃與建置企業級數據中台與資料基礎設施（含即時與批次處理架構） 設計與優化大規模 ETL Pipeline，確保資料準確性與安全性 建構高可用、高擴展的數據平台架構（Cloud + On-Prem 混合環境） 與產品、商業與工程團隊合作，定義數據模型與資料產品架構 推動資料治理、數據目錄與數據品質管理機制 導入與評估新技術，提升效能、穩定度與成本效率 【使用技術】 Programming: Python / Scala / Shell Database: MS SQL / MySQL / ClickHouse / BigQuery Data Processing: PySpark / Kafka / Airflow Cloud: GCP（含 Dataflow 等服務） Architecture: Data Lake / Data Warehouse / CDC / Streaming Visualization: Tableau / Superset 【為什麼值得加入？】 數百萬用戶、巨量交易場景，數據完整且具高度商業價值 直接參與企業數據戰略規劃，非單純維運角色 高層高度信任，具架構決策權與團隊塑造權 在高速成長的 Fintech 領域，打造可長期演進的數據平台 從 0→1 強化數據中台，是能寫進履歷的代表作

【Responsibilities】負責核心 AI 平台後端的架構規劃與技術方向制定。 建構並持續強化支援機器學習模型部署與運行的基礎系統。導入 SRE 概念並推動提升系統穩定性、擴展性及效能的相關改善專案。擔任技術領導角色，帶領 3–5 人工程團隊，包含程式碼審查與技術指導。

公司介紹 我們的客戶是一個深耕多年的大型生活風格與文化內容集團，橫跨線下實體場域與線上數位服務，長期投入於全通路經營與數位創新。 近年公司積極推動 線上線下整合（Omni-Channel）、雲端化與資料驅動決策，內部成立專責的資訊暨商業應用創新團隊，從系統架構、雲端平台到 AI 與數據應用，全面翻新核心技術基礎，目標打造可長期擴展、支撐高流量交易與多元場景的數位生態系。 這是一個穩定但正在轉型的組織，技術團隊不只是執行者，而是能實際參與架構決策、影響產品與商業走向的關鍵角色。 工作內容 團隊管理與培育：帶領約 8–12 人後端工程團隊，負責人才培育、績效管理與 Agile 流程優化 技術治理與架構演進：主導後端架構設計與 Legacy 系統現代化，平衡技術債與業務成長 系統穩定與擴展性：負責高併發交易系統，規劃雲端資源、系統監控與災難復原機制 跨部門協作：與產品、數據、營運團隊緊密合作，將商業需求轉化為可落地的技術方案 使用的技術 Backend：Golang、Ruby on Rails Cloud / Infra：GCP、Kubernetes、CI/CD、自動化部署 Architecture：Microservices、System Design、Legacy Modernization Database：PostgreSQL 為什麼值得你關注？ 影響力舞台：不只是管人，而是能實際參與核心系統與技術策略決策組織穩定＋技術轉型期：適合想在穩定環境中做「真正改變」的技術主管跨領域挑戰：結合文化內容、生活服務與數位平台，場景多元、問題真實長期發展：完整培訓制度、清楚的管理職涯路徑與海外發展機會