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產業類別： 儲配/運輸物流 職責要求 1.規劃企業資料架構藍圖（Data Architecture Blueprint） 2.設計資料模型、資料流（Data Flow）、資料倉儲（DWH）、資料湖（Data Lake）等整體架構 3.定義資料標準（Data Standard）、資料字典、資料治理策略 4.建立高效的資料平台與治理機制 5.規劃與導入 Metadata、Data Lineage、 Master Data Management 6.管控資料品質（DQ）、一致性與安全權限 7.跨部門溝通與需求分析，與產品、工程、數據科學、業務單位合作，轉化需求為技術規格 8.協助制定資料相關的 SLA、成本控制與最佳實務 9.導入雲端資料架構與最佳化 10.熟悉 AWS / Azure / GCP 等雲端平台 11.導入 Lakehouse、Streaming、ETL/ELT Pipeline 方案 12.技術導入與架構決策 13.評估並導入資料平台工具（Snowflake、BigQuery、Redshift、Databricks…） 14.針對資料量成長制定可擴展架構策略

公司介紹 這是一家在 智慧能源與 AIoT 雲端平台 領域具領導地位的軟體公司，產品已廣泛應用於再生能源監控與工業物聯網。 公司以 資料為核心資產，每日處理超過數億筆能源時序資料，持續打造高併發、高可靠性的全球級資料平台。 團隊文化極度重視技術品質與架構思維，鼓勵理性討論與開放交流。這裡沒有僵化階層，只有對卓越架構與效能極限的共同追求。 若你渴望設計能支撐 10 倍流量成長的 AIoT 系統，這將是你能充分發揮技術與影響力的舞台。 工作內容 主導設計與優化雲端 AIoT 資料流架構，涵蓋資料流、整併、儲存分析與事件偵測模組 與 SRE 團隊合作，進行架構效能瓶頸分析與轉移計畫設計，推動大規模系統效能提升 建構高可用性系統、異地備援與災難復原機制，確保雲端平台穩定性 與 Fullstack 團隊協作，推動資料流平台化，支援多產品資料需求 引領團隊進行新技術評估與雲端架構演進，持續優化資料處理策略 擔任跨部門技術橋樑，提供架構決策、團隊規劃與技術指導 使用技術 RabbitMQ、Fluentd、Elasticsearch、InfluxDB、Redis、MySQL、Spark、Kafka、SFTP/FTPS Python（主程式語言）、Golang、Rust Linux、Docker、Kubernetes（K8s）、GCP / AWS / Azure 成長挑戰 你將直接面對單日數億筆資料、百 TB 級別的儲存與分析挑戰，並主導雲端架構的演進與平台化。 在這個角色中，你不只是工程師，更是 架構決策者與技術推動者，有機會定義下一代能源 AIoT 資料平台的形貌。

We are looking for ● Are a self-driven Database Reliability Engineer with proven experience in managing large-scale database systems in production environments. ● Have a deep understanding of database architecture, performance optimization, high availability solutions, and database security best practices. ● Are following the latest industry trends in database technologies and are passionate about building reliable, scalable data infrastructure. ● Have strong automation mindset and programming skills to build tools that improve database operations and reliability. ● Understand SLI/SLO/SLA concepts and have experience implementing reliability engineering practices. Our Stack ● Relational Databases: AWS Aurora MySQL/PostgreSQL ● NoSQL Databases: MongoDB Atlas, AWS DocumentDB ● Caching Layer: AWS ElastiCache, Valkey ● Message Queue: Apache RocketMQ, RabbitMQ ● Search Engine: ElasticSearch, Mongo Atlas ● OLAP: Redshift ● Monitoring Alerting: Prometheus, Grafana, Loki, Alert Manager ● Backup Recovery: AWS Backup, Point-in-Time Recovery, Cross-Region Replication ● Database Proxy: RDS Proxy ● Infrastructure as Code: Terraform, Ansible ● CI/CD Integration: Jenkins, ArgoCD, Github Action, Helm ● Network Security: AWS VPC, Security Groups, AWS Secrets Manager ● Programming Languages: Golang, Python ● Containerization: Kubernetes

Company highlights 總部在美國紐約，在台北市有辦公室，獲得 Y Combinator 和 Two Sigma Ventures的投資兩位創辦人畢業於MIT和Wharton，後來2009年創立產品一直經營到現在，收益穩定，團隊持續擴編中彈性上班時間，外商彈性文化，100%全英文工作環境，有機會到美國總部工作！ Responsibilities Download, process, clean, and manage real estate and economic data feeds.Develop and maintain database architecture, server frameworks, security, payment processing, content hosting, and third-party data integrations.Weekly meetings with the CEO, Managing Director, and Dev Leader.

Minimum qualifications: PhD degree in Electronics and Communication Engineering, Electrical Engineering, Computer Engineering or related technical field, or equivalent practical experience. Experience with accelerator architectures and data center workloads. Experience in programming languages (e.g., C++, Python, Verilog), Synopsys, Cadence tools. Preferred qualifications: 2 years of experience post PhD. Experience with performance modeling tools. Knowledge of arithmetic units, bus architectures, accelerators, or memory hierarchies. Knowledge of high performance and low power design techniques. About the jobIn this role, you will shape the future of AI/ML hardware acceleration as a Silicon Architect/Design Engineer and drive cutting-edge TPU (Tensor Processing Unit) technology that fuels Google's most demanding AI/ML applications. You will collaborate with hardware and software architects and designers to architect, model, analyze, define and design next-generation TPUs. You will have dynamic, multi-faceted responsibilities in areas such as product definition, design, and implementation, collaborating with the Engineering teams to drive the optimal balance between performance, power, features, schedule, and cost.The AI and Infrastructure team is redefining what’s possible. We empower Google customers with breakthrough capabilities and insights by delivering AI and Infrastructure at unparalleled scale, efficiency, reliability and velocity. Our customers include Googlers, Google Cloud customers, and billions of Google users worldwide. We're the driving force behind Google's groundbreaking innovations, empowering the development of our cutting-edge AI models, delivering unparalleled computing power to global services, and providing the essential platforms that enable developers to build the future. From software to hardware our teams are shaping the future of world-leading hyperscale computing, with key teams working on the development of our TPUs, Vertex AI for Google Cloud, Google Global Networking, Data Center operations, systems research, and much more.Responsibilities Revolutionize Machine Learning (ML) workload characterization and benchmarking, and propose capabilities and optimizations for next-generation TPUs. Develop architecture specifications that meet current and future computing requirements for AI/ML roadmap. Develop architectural and microarchitectural power/performance models, microarchitecture and RTL designs and evaluate quantitative and qualitative performance and power analysis. Partner with hardware design, software, compiler, Machine Learning (ML) model and research teams for effective hardware/software codesign, creating high performance hardware/software interfaces. Develop and adopt advanced AI/ML capabilities, drive accelerated and efficient design verification strategies and implementations. Use AI techniques for faster and optimal Physical Design Convergence -Timing, floor planning, power grid and clock tree design etc. Investigate, validate, and optimize DFT, post-silicon test, and debug strategies, contributing to the advancement of silicon bring-up and qualification processes. Google is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. See also Google's EEO Policy and EEO is the Law. If you have a disability or special need that requires accommodation, please let us know by completing our Accommodations for Applicants form.

Minimum qualifications: Bachelor's degree in Computer Science, Mathematics, a related field, or equivalent practical experience. 3 years of experience with data processing software (e.g., Hadoop, Spark, Pig, Hive) and algorithms (e.g., MapReduce, Flume). Experience managing client-facing projects, troubleshooting technical issues, and working with engineering and sales services teams. Experience with database administration techniques or data engineering, as well as writing software in Java, C++, Python, Go, or JavaScript. Preferred qualifications: Master’s degree in Computer Science, Engineering, Statistics, or Mathematics. Experience with data warehouses, large-scale distributed data platforms, and data lakes. Ability to break down complex, multi-dimensional problems with structured thinking. Ability to navigate ambiguity in a fluid environment with multiple stakeholders. Excellent business and technical communication, organizational, and investigative skills. About the jobAs a Data Engineer, you will guide customers on how to ingest, store, process, analyze, explore, and visualize data on Google Cloud Platform. You will lead data migrations and transformations, partner with clients to architect scalable data processing systems, build efficient data pipelines, and resolve platform challenges. In this role, you'll collaborate with Google's strategic cloud customers and our team to successfully implement Google Cloud products.At YouTube, we believe that everyone deserves to have a voice, and that the world is a better place when we listen, share, and build community through our stories. We work together to give everyone the power to share their story, explore what they love, and connect with one another in the process. Working at the intersection of cutting-edge technology and boundless creativity, we move at the speed of culture with a shared goal to show people the world. We explore new ideas, solve real problems, and have fun — and we do it all together.Responsibilities Conduct requirements gathering and project scoping sessions with subject matter experts, business users, and executive stakeholders to discover and define business data needs. Design, build, and optimize the data architecture and extract, transform, and load (ETL) pipelines to make them accessible for Business Data Analysts, Data Scientists, and business users to enable data-driven decision-making. Work closely with analysts to productionize and scale value-creating capabilities, including data integrations and transformations, model features, and statistical and machine learning models. Drive the highest standards in data reliability, data integrity, and data governance, enabling accurate, consistent, and trustworthy data sets, business intelligence products, and analyses. Write and review end-user and technical documents, including requirements and design documents for existing and future data systems, as well as data standards and policies. Google is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. See also Google's EEO Policy and EEO is the Law. If you have a disability or special need that requires accommodation, please let us know by completing our Accommodations for Applicants form.

Logitech is the Sweet Spot for people who want their actions to have a positive global impact while having the flexibility to do it in their own way.The Team:The Operations Quality and Consumer Customer Experience (CX) team is dedicated to enhancing customer satisfaction across the entire product lifecycle, ensuring outstanding product quality and a superior consumer experience. By channeling the Voice of Consumer to internal stakeholders, the team drives continuous improvement and data-informed decision-making. Focused on fostering customer loyalty and delivering consistent excellence, the team supports Logitechs strategy of becoming an Iconic brand through exceptional products and consumer experiences.The Role: Logitech is seeking a skilled and driven Quality and CX End-to-End  AI/ML Data Analyst to work collaboratively with stakeholders, transforming both quantitative and qualitative consumer voice data into actionable insights through data mining, and driving continuous improvement initiatives as a result.The role also involves identifying opportunities to enhance product quality, elevate consumer experience, and optimize Quality and CX operations using advanced data analysis techniques.The Data Analyst will be responsible for analyzing Quality and CX data to monitor the health of product quality, consumer experience, and operational efficiency, while presenting findings to stakeholders.Your Contribution:Be Yourself. Be Open. Stay Hungry and Humble. Collaborate. Challenge. Decide and just Do. Share our passion for Equality and the Environment. These are the behaviors and values you’ll need for success at Logitech. In this role you will:Data Architecture Expertise: Serve as a subject matter expert in data structure, ensuring alignment with evolving business needs.Analytics Projects: Gather business requirements from diverse stakeholders (Engineering, Manufacturing, Consumer Experience, Quality, Finance, etc.), convert business questions into analytics initiatives, and independently perform analyses using AI/ML technologies to deliver valuable insights.Insights Communication: Extract actionable insights to support strategic decisions, presenting findings to stakeholders in a clear and impactful manner.Extract user, transaction, and other system data to create comprehensive reports and drive informed decision-making.Leverage LLM/NLP technologies to analyze customer sentiments and identify opportunities for improvement.Fostering a Data Culture: Promote a data-driven mindset across teams to enhance decision-making and operational cohesion.Process Optimization: Collaborated with business stakeholders to standardize maintain key metrics, strengthen architectural decisions, and establish scalable processes.  Cross-functional Collaboration: Build and maintain strong, cooperative relationships with stakeholders to drive impactful initiatives and ensure alignment across teams.Key Qualifications:For consideration, you must bring the following minimum skills and experiences to our team:10 years of proven experience from a similar role, including at least 5 years in data analytics or data science.Proficiency in programming tools such as Python, R.In-depth knowledge of AI/ML technologies, GenAI, Agentic AI, MCP. Exposure to Claude, GeminiExperience with data visualization tools,  preferable Tableau.Basic SQL querying knowledge for data analysis.Strong experience with project management and change management principles, methodologies and tools.Hands on approach, leading by doing and never afraid of getting ‘muddy hands’Excellent communication skills in English.Proven ability to build strong, collaborative relationships across different levels and functions.A strong sense of ownership and proven experience driving cross-functional initiatives.In addition, below skills are a plus:Certified project management professional  (PMP or similar) Education:Bachelor or Masters in Computer Science, Data Engineering, Data Science, Statistics, Analytics, or Information Systems or similar.#LI-MK1Across Logitech we empower collaboration and foster play. We help teams collaborate/learn from anywhere, without compromising on productivity or continuity so it should be no surprise that most of our jobs are open to work from home from most locations. Our hybrid work model allows some employees to work remotely while others work on-premises. Within this structure, you may have teams or departments split between working remotely and working in-house.Logitech is an amazing place to work because it is full of authentic people who are inclusive by nature as well as by design. Being a global company, we value our diversity and celebrate all our differences. Don’t meet every single requirement? Not a problem. If you feel you are the right candidate for the opportunity, we strongly recommend that you apply. We want to meet you!We offer comprehensive and competitive benefits packages and working environments that are designed to be flexible and help you to care for yourself and your loved ones, now and in the future. We believe that good health means more than getting medical care when you need it. Logitech supports a culture that encourages individuals to achieve good physical, financial, emotional, intellectual and social wellbeing so we all can create, achieve and enjoy more and support our families. We can’t wait to tell you more about them being that there are too many to list here and they vary based on location.All qualified applicants will receive consideration for employment without regard to race, sex, age, color, religion, sexual orientation, gender identity, national origin, protected veteran status, or on the basis of disability.If you require an accommodation to complete any part of the application process, are limited in the ability, are unable to access or use this online application process and need an alternative method for applying, you may contact us toll free at 1-510-713-4866 for assistance and we will get back to you as soon as possible.

Minimum qualifications: Bachelor's degree in Electrical Engineering, Computer Engineering, Computer Science, or a related field, or equivalent practical experience. 10 years of experience in ASIC development with Verilog/SystemVerilog, Vhsic Hardware Description Language (VHDL). Experience in micro-architecture and design IPs and Subsystems. Experience in ASIC design verification, synthesis, timing/power analysis, and Design for Testing (DFT). Preferred qualifications: Experience with scripting languages (e.g., Python or Perl). Experience in SoC designs and integration flows. Knowledge of bus architectures, fabrics/NoC, processor design, accelerators, or memory hierarchies.. Knowledge of high performance and low power design techniques. About the jobIn this role, you’ll work to shape the future of AI/ML hardware acceleration. You will have an opportunity to drive cutting-edge TPU (Tensor Processing Unit) technology that powers Google's most demanding AI/ML applications. You’ll be part of a team that pushes boundaries, developing custom silicon solutions that power the future of Google's TPU. You'll contribute to the innovation behind products loved by millions worldwide, and leverage your design and verification expertise to verify complex digital designs, with a specific focus on TPU architecture and its integration within AI/ML-driven systems. In this role, you will be part of a team developing Application-Specific Integrated Circuits (ASIC) used to accelerate and improve traffic efficiency in data centers. You will collaborate with members of architecture, verification, power and performance, physical design, etc. to specify and deliver high quality designs for next generation data center accelerators. You will solve technical problems with innovative micro-architecture and practical logic solutions, and evaluate design options with complexity, performance, power and area in mind.The AI and Infrastructure team is redefining what’s possible. We empower Google customers with breakthrough capabilities and insights by delivering AI and Infrastructure at unparalleled scale, efficiency, reliability and velocity. Our customers include Googlers, Google Cloud customers, and billions of Google users worldwide. We're the driving force behind Google's groundbreaking innovations, empowering the development of our cutting-edge AI models, delivering unparalleled computing power to global services, and providing the essential platforms that enable developers to build the future. From software to hardware our teams are shaping the future of world-leading hyperscale computing, with key teams working on the development of our TPUs, Vertex AI for Google Cloud, Google Global Networking, Data Center operations, systems research, and much more.Responsibilities Drive development of complex IPs and subsystems along with a team of engineers. Own micro-architecture and implementation of IPs and subsystems. Work with architecture, firmware and software teams to drive feature closure and develop micro-architecture specifications. Drive design methodology, libraries, debug, code review in coordination with other IPs Design Verification (DV) teams and physical design teams. Identify and drive power, performance and area improvements for the domains owned. Google is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. See also Google's EEO Policy and EEO is the Law. If you have a disability or special need that requires accommodation, please let us know by completing our Accommodations for Applicants form.

一、募資與資本市場策略（Fundraising Capital Markets Strategy） 主導公司募資與 IPO 各階段之整體策略規劃、財務資料準備與對外溝通。 協助 CEO 進行資本市場與產業分析，涵蓋股權結構設計、公司估值、財務模型與長期成長情境推演。 二、財務決策支持與策略夥伴角色（FPA Strategic Business Partnering） 與 CEO、COO 及各事業單位緊密合作，建立完善的年度預算、滾動式預測、差異分析與商業決策模型。 透過情境模擬與數據分析，評估新產品、定價策略、投資案與市場擴張之財務影響，並建置可供管理團隊即時掌握的決策儀表板。 三、財務會計治理、內控制度與法遵管理（Accounting, Governance Compliance） 確保帳務、稅務、結帳流程與財務報表之準確性與即時性，建立兼具合規性與營運彈性的財務與內控制度。 帶領並培育 1+4 財會團隊，優化流程與分工，打造可支撐公司高速成長與規模化發展的財務組織。 四、財務系統導入與數據架構建置（Systems Data Architecture） 主導 Oracle NetSuite 導入與優化，建立單一數據來源（Single Source of Truth），推動成本分攤、攤提與報表流程自動化，提升月結效率與數據透明度。 強化財務與業務數據的一致性，支援跨部門分析與管理決策。

At MoMo, we are not just processing transactions; we are shaping the future of finance in Vietnam. We are seeking a visionaryAnalytics Engineering Managerto bridge the gap between complex data infrastructure and actionable business insights. In this pivotal role, you will lead the charge in defining our data modeling standards, ensuring data quality, and empowering our stakeholders with a robust, self-service data platform. If you are passionate about applying software engineering best practices to data analytics and leading high-performing teams, we want you to build the future with usMô tả công việc1. Team Leadership Culture:Lead, mentor, and grow a team of talented Analytics Engineers. You will be responsible for their career development, fostering a culture of continuous learning and technical excellence.Champion the "Data as a Product" mindset, ensuring that datasets produced by the team are treated with the same rigor and reliability as customer-facing software.Drive agile processes within the data team to ensure rapid delivery of value while maintaining high standards.2. Technical Strategy Architecture:Architect and maintain a scalable data modeling layer (using tools likesemantic) that transforms raw data into reliable, documented, and accessible datasets.Define and enforce coding standards, version control practices (Git), and CI/CD workflows for analytics code.Collaborate with Data Engineering to optimize data warehouse performance (e.g., BigQuery/Lakehouse) and manage compute costs effectively.3. Data Quality Governance:Implement automated testing and observability frameworks to detect data issues before they impact downstream users.Establish clear data lineage and documentation to democratize data access across the organization.Ensure strict adherence to data privacy, security, and compliance standards—a critical requirement in the Fintech sector.4. Cross-Functional Collaboration:Partner closely with Product Managers, and Business Leaders to translate complex business requirements into technical data solutions.Act as a technical advisor, helping stakeholders understand the "art of the possible" with our data stack.Yêu cầu công việcExperience:5+ years of experience in the Data domain, with at least 2 years in a leadership or management role.Technical Mastery:Expert-level SQL skills and deep understanding of query optimization.Hands-on experience with Cloud Data Warehouses (Google BigQuery)Workflow Orchestration:Hands-on experience with orchestration tools such asAirflow, n8n.You should be capable of designing complex, dependency-aware pipelines that are resilient to failure.BI Semantic Layer Integration:Deep understanding of how data is consumed by BI tools (e.g.,Looker...). Ability to design the 'Semantic Layer' to ensure consistent metrics across the organization.Soft Skills Culture FitStakeholder Management:"Ability to manage expectations with C-level executives and negotiate priorities effectively in a fast-paced environment."Talent Acquisition:"Experience in recruiting top-tier engineering talent and building a diverse, high-performing team from the ground up."