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數據工程負責人（Head of Data Engineering），負責領導設計和實施數據基礎設施，以支持快速擴展的加密貨幣交易所業務。主要目標是構建高效、可擴展且安全的數據系統，處理實時交易數據、用戶行為數據和市場數據。 主要職責 數據架構與基礎設施設計 領導設計可擴展、高性能的數據系統，用於存儲和處理大量交易數據、用戶行為日誌、市場數據和交易活動。 確保系統高可用性並優化低延遲訪問。 實時數據處理 構建和管理高吞吐量的實時數據流系統，處理加密貨幣交易、市場數據和用戶活動。 確保數據攝取和處理的延遲最小化，支持及時決策和交易執行。 數據整合與管理 設計系統以攝取、存儲和整合多源數據（如交易數據、用戶日誌、外部市場數據）。 規範化和組織數據，支持分析和商業智能需求。 用戶與交易數據存儲 制定策略存儲大量用戶行為數據（交易歷史、登錄活動等）和交易數據（訂單簿、提款等）。 確保數據存取快速、安全且成本效益高。 數據治理、質量與合規性 建立數據治理實踐，確保數據完整性、質量和符合法規（如GDPR、CCPA、AML/KYC）。 實施數據驗證、清洗和審計流程。 成本優化 設計兼顧性能與成本效益的系統，使用分片、數據分區和壓縮等技術。 確保數據基礎設施隨業務增長可擴展且成本可控。 領導與團隊管理 帶領數據工程團隊，推動最佳實踐和性能標準，培養合作文化。 提供指導和職業發展支持。 跨部門協作 與產品、市場、研究、安全和合規團隊合作，確保數據基礎設施滿足業務多樣化需求。 支持產品創新、用戶行為分析和法規合規的分析框架。 技術評估與選擇 持續評估新興數據技術，選擇最適合管理交易和用戶數據的工具。 確保數據基礎設施與公司戰略目標一致。

MoMo is the leading mobile payments provider in Vietnam, committed to improving the lives of every Vietnamese through technological innovation. As our business continues to expand, were looking for an experienced Data Engineer to join our Data Platform team.At MoMo, we emphasize smart, efficient, and excellent execution, with a strong focus on data quality. Our data platform delivers critical insights for:Business and app performance monitoringMachine learning products including recommendation systems, personalization, risk scoring, fraud detection, targeted promotions, and financial servicesWere also building a next-generation hybrid data platform across multiple cloud providers, giving us greater control over both cost and technologyMô tả công việcWith MoMo's AI-first mission, we are designing and building a self-serve data platform to empower both internal teams and external partners. This platform allocates resources based on users’ needs to support:Ingesting data from diverse sources — either in batch or streaming, using both pull and push mechanisms;Developing and deploying resilient data pipelines across the data lake, data warehouse, and streaming systems;Delivering high-quality, derived datasets to downstream tools such as BI solutions (e.g., Apache Superset, Google Data Studio), via multiple delivery methods including APIs, datasets, and streaming data;Monitoring data quality throughout all data pipelines in the platform to ensure high-quality data, resulting in better decision-making, accurate reporting, and reliable machine learning outputs;Tracking and optimising resource usage for efficiency;Additionally, we are building Data Management Systems that enable the Data Governance team and data consumers to:Manage the full data lifecycle within the big data platform;Explore the MoMo data ecosystem independently;Provide a single source of truth with high data quality to downstream consumers;Track and manage infrastructure costs across major projects, teams, and departments.Yêu cầu công việcBachelor’s degree in Computer Science, Engineering, or a related field;A problem solver with a strong sense of ownership and accountability — not just a task executor;5+ years of experience working as a Data Engineer and 1+ year of experience working as leader;Curious and committed to lifelong learning, with a passion for solving business problems through engineering, improving service quality and usability, and maintaining a strong customer focus;Strong foundation in computer science fundamentals, including data structures, algorithms, database systems, and data modelling techniques;Proficient in at least one of the following languages: SQL, Python, JVM-based languages;Experience with databases such as PostgreSQL, MySQL, ClickHouse, DuckDB, etc;Skilled in analysing, designing, implementing, and optimising Data Vault or Dimensional Modeling for performance and cost;Hands-on experience with infrastructure platforms — cloud-based (e.g., GCP, AWS) or on-premise — and container orchestration using Kubernetes;Experience with data storage and processing engines like Apache Spark, Apache Flink, and StarRocks;Experience with Google Cloud Platform or Amazon Web Services is a plus.

Minimum qualifications: Bachelor's degree or equivalent practical experience. 10 years of experience working with data infrastructure and data models by performing exploratory queries and scripts. 5 years of experience coding in one or more programming languages, and designing data pipelines, and dimensional data modeling for synch and asynch system integration and implementation using internal and external stacks. 3 years of experience in a people management, supervision, or team leadership role. Preferred qualifications: 10 years of experience in business intelligence, analytics, and data engineering related fields. 5 years of experience developing project plans and delivering projects on time within budget and scope. 5 years of experience partnering with stakeholders (e.g., users, partners, customer), and managing stakeholders/customers. 5 years of experience with statistical methodology and data consumption tools such as business intelligence tools, collabs, jupyter notebooks, Tableau, Power BI, DataStudio, and business intelligence platforms. 3 years of experience with Machine Learning for production workflows. Experience in Programming and SQL. Experience building, developing, and leading a team. About the jobAs a data engineering manager, you will lead and empower a high-performing team of data engineers, fostering a culture of technical excellence, continuous mentorship, and process innovation. You will act as a strategic partner for various stakeholders, prioritizing initiatives that drive automation, enhance data infrastructure, and ensure the delivery of high quality data products. Ultimately, your leadership will directly enable the YouTube content partnerships and creator ecosystem, equipping business leadership with the critical insights needed to optimize the effectiveness and efficiency of the YouTube partner-facing business teams.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 Establish and clearly articulate team strategy that drives the organization's overarching goals and decision-making across functional groups. Define the technical goal continuously adapting it to anticipate future business requirements and infrastructure scalability. Build and refine robust internal processes to govern project prioritization, the end-to-end development lifecycle, and ongoing operational support. Lead a high-performing team of data engineers by providing technical guidance, establish best practices, and manage task allocation through an agile roadmap that adapts to evolving stakeholder demands. Partner effectively with cross-functional stakeholders. Steer the complete lifecycle of data products, direct your team in the design, development, and ongoing maintenance of data assets specific to YouTube partnerships data. Shape the strategic narrative for executive leadership by delivering insights to key decision-makers, automating the insight-gathering process, and translating complex technical analyses into clear communications. 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, Information Systems, a related technical field, or equivalent practical experience. 5 years of experience in data analysis, database querying (e.g., SQL), and BigQuery. Experience in scripting, working with code, or system design, and in leading projects. Experience mentoring and leading junior engineers. Experience in defining and implementing data governance policies, procedures, and standards. Preferred qualifications: Experience with Data Center Technology or Supply Chain. Experience with data analysis at scale, including statistics, and machine learning model development (data preparation, model selection, evaluation, tuning). Experience in scripting languages like Python for data manipulation, analysis, and automation. Experience with a wide range of data engineering and data governance tools and technologies, including cloud platforms (e.g., GCP), data warehousing solutions, data quality tools, and metadata management systems. Experience with collaborative coding and version control. Knowledge of data privacy regulations and compliance requirements. About the jobThe Google Cloud Consulting Professional Services team guides customers through the moments that matter most in their cloud journey to help businesses thrive. We help customers transform and evolve their business through the use of Google’s global network, web-scale data centers, and software infrastructure. As part of an innovative team in this rapidly growing business, you will help shape the future of businesses of all sizes and use technology to connect with customers, employees, and partners. Google Cloud accelerates every organization’s ability to digitally transform its business and industry. We deliver enterprise-grade solutions that leverage Google’s cutting-edge technology, and tools that help developers build more sustainably. Customers in more than 200 countries and territories turn to Google Cloud as their trusted partner to enable growth and solve their most critical business problems.Responsibilities Design, build, and maintain scalable and reliable data pipelines to ingest, process, and store data from various sources.This includes implementing robust data quality checks and monitoring systems to ensure data accuracy, integrity, and reliability. Write complex SQL queries for data extraction and transformation, enable both ad-hoc analysis and automated reporting. Conduct quantitative data analysis to support business decisions and identify opportunities. Partner with business stakeholders to understand their data needs, translate them into actionable technical designs and solutions.This includes collaborating with engineers, program managers, and product managers. Create and maintain dashboards and reports to provide actionable insights to stakeholders. Effectively communicate insights and drive the implementations. Develop tools and systems to automate data processes, and increase overall efficiency. Proficiency in programming languages (SQL, Python), and produce readable and well-structured code. 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 or equivalent practical experience. 10 years of experience working with data infrastructure and data models by performing exploratory queries and scripts. 5 years of experience coding in one or more programming languages, and designing data pipelines, and dimensional data modeling for synch and asynch system integration and implementation using internal and external stacks. 3 years of experience in a people management, supervision, or team leadership role. Preferred qualifications: 8 years of experience in data analysis, database querying (e.g., SQL), and BigQuery. 5 years of experience with statistical methodology and data consumption tools such as business intelligence tools, collabs, jupyter notebooks, Tableau, Power BI, Data Studio, and business intelligence platforms. 5 years of experience in a leadership role with direct reports. Experience with a wide range of data engineering and data governance tools like cloud platforms, data warehousing solutions, data quality tools, and metadata management systems. Experience with data analysis at scale, including statistics, and machine learning model development. Familiarity with data center technology or supply chain. About the jobThe Google Cloud team helps companies, schools, and government seamlessly make the switch to Google products and supports them along the way. You listen to the customer and swiftly problem-solve technical issues to show how our products can make businesses more productive, collaborative, and innovative. You work closely with a cross-functional team of web developers and systems administrators, not to mention a variety of both regional and international customers. Your relationships with customers are crucial in helping Google grow its Cloud business and helping companies around the world innovate. The Cloud Supply Chain Data Engineering, End-to-End Systems and Analytics team is chartered to provide the most efficient systems and analytics enabling faster decision making and throughput time for Google Cloud's Supply Chain. As Google Cloud continues to scale, this team’s work will contribute to the ongoing product, process and capability growth to ensure Google can continue to meet market and competitive goals.Google's projects, like our users, span the globe and require managers to keep the big picture in focus. As a TPM, Data Engineering, you will lead the next generation of business intelligence platforms, reporting, and intelligence globally for Google's Server Operations teams. You will work with internal and external customers to build cascading dashboards and reports, diagnostic analytics, and owning a server operations measurement framework for effective decision making.Google Cloud accelerates every organization’s ability to digitally transform its business and industry. We deliver enterprise-grade solutions that leverage Google’s cutting-edge technology, and tools that help developers build more sustainably. Customers in more than 200 countries and territories turn to Google Cloud as their trusted partner to enable growth and solve their most critical business problems.Responsibilities Lead a team of individuals. Set and communicate individual and team priorities that support organizational goals. Meet regularly with individuals to discuss performance and development, and provide feedback and coaching. Design and build data processing systems with a particular emphasis on security, compliance, scalability, efficiency, reliability, and portability. Create or consult in creating data visualizations using Business Intelligence (BI) tools (e.g., Data Studio, Tableau, etc.). Develop and maintain data models, pipelines, and exchange formats to assist in the visualization, analysis, and interpretation of data and for use of data in ML training/models. Provide ongoing support for data users through maintenance of reports, queries, and dashboards, fielding user questions, authoring documentation, and delivering training. Develop tools and systems to automate data processes, facilitate faster turnarounds, and increase overall efficiency. 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.

【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

公司介紹 這是一家穩健經營超過半世紀的金融龍頭企業，近年積極啟動大規模數位轉型，成立「科技創研中心」，整合數據工程、AI研發與雲端治理三大領域，打造具前瞻性的金融科技基礎。 公司正投入建構企業級 Data Lakehouse 與 LLM 平台，結合生成式AI、資料虛擬化及雲端運算，以數據驅動服務創新與決策升級。 對於希望在大型體系中主導AI工程與金融數據轉型的中高階技術主管而言，這是兼具穩定與影響力的關鍵舞台。 工作內容 領導 Data AI 工程團隊（約5人），規劃與執行數據平台及AI/LLM架構策略 建構並優化 Data Lakehouse、Denodo 虛擬化平台與資料整合流程 推動企業AI/LLM平台與MLOps落地，確保模型開發與部署效能 跨部門協作，將AI技術導入金融服務應用，提升營運效率與決策品質 持續追蹤AI與雲端新技術，制定技術藍圖與團隊成長方向 使用技術 Data Lakehouse（Databricks、Iceberg、Hudi 等） Denodo Data Virtualization Python / Java / SQL 雲端平台：AWS / GCP / Azure MLOps、LLM Fine-tuning、Prompt Engineering

Established in 1987 and headquartered in Taiwan, TSMC pioneered the pure-play foundry business model with an exclusive focus on manufacturing its customers’ products. As of 2024, TSMC serves more than 500 customers and manufactures over 11,000 products for high-performance computing, smartphones, the Internet of Things (IoT), automotive, and digital consumer electronics. It is the world’s largest provider of logic ICs, with an annual capacity of 16 million 12-inch equivalent wafers. TSMC operates fabs in Taiwan as well as manufacturing subsidiaries in Washington State, Japan and China, and the Company began construction on a specialty technology fab in Dresden, Germany, in 2024. In Arizona, TSMC is building three fabs, with the first starting 4nm production in 2025, the second by 2028, and the third by the end of the decade. Are you a creative IT professional with strong technical aptitude who embraces changes and is passionate about data and information? We invite you to join our highly innovative data engineering team which is constantly designing, developing, and delivering high quality solutions for our customers. As a data engineer, you will have opportunities to work in a dynamic and fast-paced environment to collaborate with business functions to design solutions. You will translate business requirements into technical needs, connect and automate data pipelines, and deliver data architecture and data governance solutions. Responsibility: Perform IT system architecture design, new technology research, and provide recommendation.Design and implement optimal data pipeline architecture (considered high data volume, data governance, etc.).Work with PRODUCT/BIZ teams to assist with new data platform re-engineering or data-related technical issues.DataOps high availability NoSQL DB (e.g.: Cassandra, S3/MinIO, MariaDB, etc.) on K8s environment.

Minimum qualifications: Bachelor's degree or equivalent practical experience. 3 years of experience in a data engineering, data infrastructure, or data analytics role. Experience with database administration techniques or data engineering, as well as writing software in Java, C++, Python, Go, or JavaScript. Preferred qualifications: Experience with data warehouses, including data warehouse technical architectures, infrastructure components, ETL/ELT, and reporting/analytic tools and environments. Experience with data analysis, including statistics, and ML model development (data preparation, model selection, evaluation, tuning). Experience in scripting languages like Python for data manipulation, analysis, and automation. Ability to monitor, troubleshoot, and tune data systems and pipelines to improve efficiency. Ability to develop tools and systems to automate data processes, and increase overall efficiency, with proficiency in programming languages (e.g., SQL, Python), producing readable and well-structured code. Ability to deliver and maintain data projects from conception to production. About the jobGoogle Play provides apps, games, and digital content services that bring Android devices to life. The Play Store serves over four billion users around the world, and is a critical driver of Google’s overall revenue growth. The Play Data Science Analytics (DSA) team works on a variety of challenging data science projects to drive product and go-to-market decisions for Play. Our vision is to Power Play’s growth by building a deep understanding of our users and developers, enabling data-driven decision making, through strategic insights, thought leadership, and unified data foundations.As a Data Engineer on the Play Data Science Analytics team, you will take a significant role in designing and building the next generation of our data infrastructure. You will be responsible for architecting, implementing, and optimizing complex, scalable data pipelines, moving beyond basic development to own key components of our data warehouse. This role requires a technical expert who can handle massive datasets, write highly efficient SQL and Python code, and collaborate effectively with senior stakeholders and engineers. You will build innovative data foundations and AI-driven insights solutions while helping to define the standards and best practices that elevate the entire team, driving data quality and AI-readiness initiatives.ResponsibilitiesDesign, build, and maintain scalable data pipelines to ingest, process, and store data from various sources. Implement data quality checks and monitoring to ensure accuracy and integrity.Write complex SQL queries for data extraction and transformation to enable ad-hoc analysis and automated reporting. Conduct quantitative analysis to support business decisions.Develop and manage scalable data foundations and models specifically designed to support AI/ML initiatives and AI-driven insights.Develop, test, and deploy intelligent agents using Python and the Google ADK framework to automate tasks like data analysis and system orchestration.Partner with executive stakeholders and data scientists.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 Statistics, Mathematics, Data Science, Engineering, Physics, Economics, or a related quantitative field. 10 years of experience using analytics to solve product or business problems, performing statistical analysis, and coding (e.g., Python, R, SQL), or 8 years of experience with a Master's degree. Preferred qualifications: Master's degree in Statistics, Mathematics, Data Science, Engineering, Physics, Economics, or a related quantitative field. 12 years of experience using analytics to solve product or business problems, performing statistical analysis, and coding (e.g., Python, R, SQL). 5 years of experience in extracting and manipulating large datasets and designing ETL flows. About the jobHelp serve Google's worldwide user base of more than a billion people. Data Scientists provide quantitative support, market understanding and a strategic perspective to our partners throughout the organization. As a data-loving member of the team, you serve as an analytics expert for your partners, using numbers to help them make better decisions. You will weave stories with meaningful insight from data. You'll make critical recommendations for your fellow Googlers in Engineering and Product Management. You relish tallying up the numbers one minute and communicating your findings to a team leader the next. The Business Platform for Sales and Support (BPSS) team is part of Enterprise Platforms and Ecosystems (EPE) within Corporate Engineering (CorpEng), with a mission to build products for Google's internal contact center business for sales and support. We are a fast-moving, high-impact team that operates like a startup, with the resources of Google behind us. As a Data Scientist on this team, you will work closely with product and engineering teams throughout the entire development process to help build and shape next-generation GenAI products for our users.Responsibilities Define, own, and evolve product success metrics, as well as report, analyze, and forecast key product trends to make recommendations for improvement. Perform data exploration to understand user behavior and identify opportunities for improving products. Apply technical expertise in observational data analysis, modeling, and causal inference to answer product questions. Lead the design, analysis, and interpretation of product experiments to measure the causal effects of product changes. Partner with Product, Engineering, and other cross-functional teams to influence, prioritize, and support product strategy. This involves framing and solving ambiguous business problems, acting as a thought partner, influencing a wide range of product and engineering stakeholders. 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.