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Minimum qualifications: Bachelor’s degree or equivalent practical experience. 5 years of experience in program management, project management, or a similar role. Experience using data and key metrics to measure project success and inform future decisions. Preferred qualifications: Ability to manage multiple projects simultaneously and meet deadlines with strong organizational and time-management skills. Ability to work effectively with cross-functional teams, particularly with engineering, product, and operations stakeholders. Excellent investigative and problem-solving skills, with a demonstrated ability to navigate ambiguity and resolve project blockers. Excellent written and verbal communication skills, with the ability to create clear documentation and present status updates to various audiences. About the jobThe Global Business Applied AI - Strategic Programs for Automation, Resolution and Knowledge (GBAI-SPARK) team is a crucial part of our GBO's commitment to innovation and efficiency. GBAI is responsible for architecting and delivering AI-powered, intuitive, and connected solutions that amplify the value we bring to our customers and partners. GBAI-SPARK's core focus is on driving programs in technology and AI within our Support ecosystem, specifically through automation, customer support resolutions, and knowledge management.Responsibilities Manage the entire lifecycle of assigned programs, from initial scoping and requirements gathering to launch and post-launch analysis. Develop and maintain detailed project plans, including scope, milestones, timelines, dependencies, and resource needs. Own the execution and successful delivery of your assigned initiatives on the strategic tool roadmap. Develop and provide regular, clear, and concise status updates on your programs to stakeholders and the management team. Identify, track, and actively work to resolve project blockers and issues before they impact timelines. Serve as the direct point of contact for and partner closely with Product, Engineering, and Operations teams to ensure the successful design, development, and implementation of new tools. 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.

【公司描述】 我們是一家全球領先的數字資產交易與支付科技公司，致力於打造安全、高效的金融基礎設施。 目前，我們正在尋找資深數據工程師，負責獎勵與財務數據項目的開發與優化，與國際團隊合作，打造高效且可擴展的數據平台。 【Company Overview】 A global leader in digital asset exchange and payment technology, committed to building secure and efficient financial infrastructure. The company is now hiring a Senior Data Engineer to drive development and optimization of data systems for rewards and financial operations. This role involves close collaboration with international teams to build scalable and reliable data platforms. 【職位亮點】 ✅ 年薪 USD $60,000–80,000，具競爭力的薪資與成長空間 ✅ 國際化團隊，與全球頂尖技術專家合作 ✅ 參與高併發、即時數據處理專案，發展大規模數據基礎設施 【Role Highlights】 ✅ Competitive salary (USD $60K–80K) with strong career growth ✅ Join a global team and work with top engineers from around the world ✅ Build high-throughput, real-time data infrastructure at scale 【職位職責】 🔹 數據平台與管道開發：設計與維護穩定高效的數據架構 🔹 數據倉儲建置與優化：支援離線與即時數據的儲存與檢索 🔹 大數據處理與轉換：使用 Hadoop、Spark、Flink 等技術 🔹 跨部門協作：與財務、獎勵、技術團隊合作，提供數據解決方案 【Responsibilities】 🔹 Design and maintain stable, high-performance data platforms and pipelines 🔹 Develop and optimize offline and real-time data warehouses 🔹 Process and transform large data sets using Hadoop, Spark, or Flink 🔹 Collaborate cross-functionally with Finance, Rewards, and Engineering teams to deliver data-driven solutions 【職位要求】 ✔ 3–8 年數據平台或數據工程經驗 ✔ 精通 Hadoop、Spark、Flink 等大數據工具 ✔ 熟悉 Python / Scala / Java 至少一種程式語言 ✔ 熟悉數據倉儲與 ETL（離線與即時）開發經驗 ✔ 有 Airflow 經驗者佳 ✔ 英文流利，能與國際團隊順利溝通 【Requirements】 ✔ 3–8 years of experience in data platform or pipeline engineering ✔ Proficient in big data tools: Hadoop, Spark, Flink ✔ Strong programming skills in at least one of: Python, Scala, or Java ✔ Solid understanding of data warehousing and ETL (offline real-time) ✔ Experience with Airflow is a plus ✔ Fluent in English with strong communication skills for working across global teams---------------------------------------------------------------------- 若您對此職位感興趣，請立即聯繫，讓我為您介紹更多詳細資訊！ ▶︎ 聯繫人：招募顧問 Owen Wu▶︎ LINE： https://line.me/ti/p/ICjS8Jx0Dq▶︎ LinkedIn： https://www.linkedin.com/in/owen-wu-1023a41a4/

・與產品、風控、運營團隊協作，針對業務需求定義資料模型與監控指標・建置 ETL 流程，收集與清洗來自平台的行為數據（如下注記錄、轉碼、點擊行為）・開發與維護異常偵測模型（如洗碼對打、機器人行為、套利用戶）・利用機器學習或統計模型預測玩家留存、LTV、流失風險・設計風控策略，提升平台資金與行爲風險控制能力・定期產出分析報告，提出可行的產品或營運優化建議

awoo 阿物科技以深厚的 SEO 顧問專業起家，成功轉型為服務全球逾 16,000 家企業的 MarTech 領導品牌。面對生成式 AI 改寫企業營運與消費者行為的巨浪，awoo 結合「頂尖 AI 技術」與「十年顧問實戰經驗」，推出具備市場前瞻性的 GEO (Generative Engine Optimization) 與 LLMO 解決方案。我們致力於協助企業在大型語言模型主導的未來，不僅被 AI 看見，更被精準引用與推薦，將 AI 轉化為企業持續成長的最佳 Agent。【可接受農曆年後入職】 Major Duties and Responsibilities： 產品落地與協作：負責開發和優化 AI 產品與服務，從 PoC 到產品化，跨部門合作提出創新解決方案，推動 AI 產品落地。效能優化：維運現有系統，分析並解決服務和算法的效能瓶頸。ML/Data Pipeline：設計與建立可擴展的 Pipeline 自動化流程，提升開發和部署效率。 Qualifications： 具備 5 年以上軟體開發經驗，3 年以上 AI 產品研發經驗。熟悉自然語言處理（NLP）、生成式 AI 相關技術（LLM, RAG, Prompt/Context Engineering），使用開源套件或自行開發算法（Transformers, LangChain, LangGraph, DSPy, TensorFlow, PyTorch, Scikit-Learn）。具備模型的開發、訓練、部署、優化的完整實務經驗。具備使用 Container 和 Kubernetes 的開發與部署經驗。熟悉向量資料庫與 Embedding 模型，確保系統效能與可擴充性。熟悉分散式計算與查詢引擎（如 Spark、Trino、Clickhouse），具有處理大量資料處理開發與維運經驗。熟練 Git, Linux, Python, Docker, SQL，能以 FastAPI 開發高效服務。 Nice-to-Have： 雲平台經驗，如 GCP, AWS, Azure。具有 LLM/SLM Finetuning 實務經驗。MLOps/LLMOps 專案經驗，以量化指標來衡量模型和產品的成效。規劃與實作 CI/CD 自動化流程。具備推薦、搜尋或貼標系統的產品化經驗 擅⻑工具（JD 標籤） 程式與開發：Python, Git, Linux, SQL, FastAPIGenAI：RAG, Prompt Engineering, Context Engineering, Agent資料與運算：Airflow, Spark, Trino, Vector Database, Qdrant平台與部署：Docker, Kubernetes, Cloud, GCP, AWS, Azure

【關於 Pinkoi Data Squad】我們是 Pinkoi 的資料團隊，其目標為打造有效的數據平台，同時確保資料的品質與穩定性，讓資料在 Pinkoi 發揮最大的價值。Data Engineer 將與 Business Analyst／ML Engineer 緊密合作，透過數據探索問題、規劃後續的 Data Pipeline（資料管線） 實作，並提供 End-to-end 的 Data Solution，以擴展公司各部門的數據分析能力，並完善整體商業智慧系統。你需要負責的工作內容與產品、行銷、廣告等分析師與商業團隊合作，理解需求並規劃合適的 Data Pipeline。設計、實作與維護 ETL/ELT 流程，確保資料品質、穩定性與新鮮度。建立與優化資料模型，支援報表、分析與機器學習等多種場景。持續迭代並優化資料基礎建設，提升可擴展性與維運效率。建立監控與告警機制，確保 Pipeline 成功率與資料 SLA。我們希望你有的經驗跟特質對 Big Data 和 Data-driven engineering 有極大的熱情。瞭解 ETL 或 ELT 的流程，並具備 Data Modeling 跟開發 Data Pipeline 的能力。具備與產品 / 行銷團隊合作的經驗，並可與商業分析師、資料工程師，以及機器學習工程師協同合作。樂於學習最新的技術，隨時充實自我的專業技能。對大型語言模型（LLM）保持開放與好奇，願意學習並嘗試將其應用於資料工程工作（如：資料清理、欄位補全、文件生成、自動化測試），以探索新工具如何提升效率與使用者體驗。應徵條件數學 / 統計 / 資訊 / 資料科學相關科系畢業，或具備同等專業能力。一年以上數據分析或數據工程相關工作經驗。熟悉 Python、Scala、Java 等任何一種程式語言，Pinkoi 主要用 Python。熟悉 GNU/Linux 系統，Pinkoi 用 Ubuntu。熟悉關聯式資料庫的運用，例如 MySQL。加分條件熟悉廣告歸因邏輯，或具備相關數據處理經驗。具備使用者行為數據處理經驗。具有操作或架設 BI 工具的相關經驗。如 Superset、Tableau、Looker Studio，Pinkoi 使用 Superset 和 Redash。具有分散式運算的相關知識，例如 Spark、Hadoop、Hive 等一種或多種相關技術，Pinkoi 主要用 PySpark。熟悉雲端服務，例如 AWS Athena、S3、Glue，GCP BigQuery 等，Pinkoi 主要用 AWS。了解 dbt 的基礎架構和應用方式，如建立資料模型、撰寫測試、建立巨集等等。有將 LLM 應用於資料工程場景的經驗，例如規則抽取、欄位對齊與補全、文件／Data Catalog 生成、資料品質檢查等。＃不用想了，趕快來當個 Pinkoi 人如果你有信心能夠勝任這份工作，歡迎提供你的個人履歷與小作業，即刻應徵！

我們正在尋找一位具備深厚AI技術背景與架構設計能力的資深AI架構師／工程師，能夠主導公司AI技術的發展方向，並在各個業務環節與產品中導入AI解決方案，提升整體營運效率與產品競爭力！ 【工作內容】 • 擔任AI技術領導角色，制定AI技術藍圖與發展策略 • 主導AI架構設計，涵蓋資料處理、模型訓練、部署與監控 • 與產品、業務 等跨部門合作，發掘AI應用場景並提出創新解決方案 • 評估並導入最新AI技術（如生成式AI、LLM、Vision AI、AutoML等） • 指導團隊成員進行AI模型開發與優化，提升團隊技術能力 • 參與AI相關專案的技術評估、PoC、落地實施與效益分析 【必要條件】 • 資訊工程、電機、統計、數學或相關領域碩士以上學歷 • 5年以上AI／機器學習／深度學習相關工作經驗 • 熟悉主流AI框架（如 PyTorch、TensorFlow、Transformers、LangChain 等） • 具備大型AI系統架構設計與部署經驗（雲端／地端皆可） • 熟悉資料工程流程與工具（如 Spark、Airflow、Data Lake、ETL） • 具備MLOps實務經驗者佳（如 MLflow、Kubeflow、Docker、Kubernetes） • 具備良好溝通能力與跨部門協作經驗

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, we're 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 servicesWe're 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 mechanismsDeveloping and deploying resilient data pipelines across the data lake, data warehouse, and streaming systemsDelivering 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 dataMonitoring 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 outputsTracking and optimising resource usage for efficiencyAdditionally, 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 platformExplore the MoMo data ecosystem independentlyProvide a single source of truth with high data quality to downstream consumersTrack and manage infrastructure costs across major projects, teams, and departmentsYêu cầu công việcBachelor’s degree in Computer Science, Engineering, or a related fieldA problem solver with a strong sense of ownership and accountability — not just a task executor5+ years of experience working as a Data Engineer and 1+ year of experience working as leaderCurious and committed to lifelong learning, with a passion for solving business problems through engineering, improving service quality and usability, and maintaining a strong customer focusStrong foundation in computer science fundamentals, including data structures, algorithms, database systems, and data modelling techniquesProficient in at least one of the following languages: SQL, Python, JVM-based languagesExperience with databases such as PostgreSQL, MySQL, ClickHouse, DuckDB, etcSkilled in analysing, designing, implementing, and optimising Data Vault or Dimensional Modeling for performance and costHands-on experience with infrastructure platforms — cloud-based (e.g., GCP, AWS) or on-premise — and container orchestration using KubernetesExperience with data storage and processing engines like Apache Spark, Apache Flink, and StarRocksExperience with Google Cloud Platform or Amazon Web Services is a plus.

Introduction: We Are: Drive technology innovations that shape the way we live and connect. Our technology drives the Era of Pervasive Intelligence, where smart tech and AI are seamlessly woven into daily life. From self-driving cars and health-monitoring smartwatches to renewable energy systems that efficiently distribute clean power, Synopsys creates high-performance silicon chips that help build a healthier, safer, and more sustainable world. Internship Experience: At Synopsys, interns dive into real-world projects, gaining hands-on experience while collaborating with our passionate teams worldwide—and having fun in the process! You'll have the freedom to share your ideas, unleash your creativity, and explore your interests. This is your opportunity to bring your solutions to life and work with cutting-edge technology that shapes not only the future of innovation but also your own career path. Join us and start shaping your future today! Mission Statement: Our mission is to fuel today’s innovations and spark tomorrow’s creativity. Together, we embrace a growth mindset, empower one another, and collaborate to achieve our shared goals. Every day, we live by our values of Integrity, Excellence, Leadership, and Passion, fostering an inclusive culture where everyone can thrive—both at work and beyond. We are seeking talented students who are willing to learn and consistent in long-term goals to prepare for the next generation of professional IC Design engineers at Synopsys. What You'll Be Doing: You will join in the Internship Program under the guidance from our dedicated and experienced engineers, includes Stage 1: Fundamental Training Training for fundamental knowledge of IC designTraining for both Theory and Lab to understand the basic of key jobs of IC design (Digital, Analog)All training results from interns will be reviewed and interns will be advised for the best suitable jobs in IC design. Stage 2: Mini Project Mini project contains all the basic requirements of a real project which helps interns get familiar with the real jobs after this training.Project results will be reviewed and interns with good evaluations will have a chance to be considered for the full-time position at Synopsys. What You'll Get: Be offered intern allowance and provided working equipment.Be trained and coached by many experts from around the world and a talented engineering team in the local office.Opportunity to expose to a professional, innovative working environment in one of the certified Great Place to Work offices of Synopsys. Opportunity to get in touch with the complete design flow of a real complicated Analog Mixed Signal Design from specification to silicon.Chance to work with bleeding-edge technologies that enable Data Center, AI/ML, 5G applications.Be provided a Growth career path for self-development.

Minimum qualifications: Bachelor's degree or equivalent practical experience. 5 years of experience in designing data pipelines, and dimensional data modeling for synch and asynch system integration and implementation using internal (e.g., Flume, etc.) and external stacks (e.g., DataFlow, Spark, etc.). 5 years of experience with coding in one or more programming languages. 5 years of experience in working with data infrastructure and data models by performing exploratory queries and scripts. Preferred qualifications: Master’s degree in Computer Science, Engineering, Statistics, Math, or a related quantitative field. Experience with data warehouses and maintaining distributed data platforms, and data lakes. Ability to break down multi-dimensional problems. Ability to navigate ambiguity and work in a changing environment with multiple stakeholders. Excellent business and technical communication, organizational, and investigative skills. About the jobIn this role, you will be part of a community of analytics professionals who work on projects ranging from building and maintaining data platforms, developing data pipelines that help run the business, build tools to analyze the content partnerships and creator ecosystem. You will be responsible for democratizing YouTube’s business data, helping business leaders make sense of business operations through accurate business intelligence.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 Build and maintain data platforms to enable data reliability, data integrity, and data governance, enabling accurate and consistent data sets. Design, build, and optimize the data architecture and extract, transform, and load (ETL) pipelines. Conduct requirements gathering and project scoping sessions with subject matter experts, business users, and executive stakeholders to discover and define business data needs. Work with analysts to productionize capabilities, including data integrations and transformations, model features, and statistical and machine learning models. 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. Engage with the analyst community, communicate with analysts to understand user journeys and data sourcing inefficiencies, advocate best practices and lead analyst trainings. 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 Engineering, Computer Science, a related field, or equivalent practical experience. 8 years of experience in technical consulting or project/program management in corporate IT, professional IT services, or product development. 8 years of experience in coding with one or more programming languages (e.g., Java, C/C++, Python). Experience in data retrieval, data engineering, data mining, and machine learning. Experience in managing external customers or stakeholders. Preferred qualifications: Experience in working with recommendation engines, data pipelines, and distributed machine learning. Knowledge of the auxiliary practical concerns in production Machine Learning (ML) systems. Knowledge of data warehousing concepts, including data warehouse technical architectures, infrastructure components, Extract, Transform, and Load/Extract, Load and Transform (ETL/ELT), and reporting/investigative tools and environments (e.g., Apache Beam, Hadoop, Spark, Pig, Hive, MapReduce, Flume). Excellent organizational, investigative, and collaboration skills. About the jobThe Google Cloud Platform team helps customers transform and build what's next for their business — all with technology built in the cloud. Our products are developed for security, reliability and scalability, running the full stack from infrastructure to applications to devices and hardware. Our teams are dedicated to helping our customers — developers, small and large businesses, educational institutions and government agencies — see the benefits of our technology come to life. As part of an entrepreneurial team in this rapidly growing business, you will play a key role in understanding the needs of our customers and help shape the future of businesses of all sizes 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 Work with customers to identify opportunities to apply machine learning in their business. Design and implement machine learning solutions for customer use cases, leverage core Google products including TensorFlow, DataFlow, and Artificial Intelligence (AI) Platform. Manage and grow a team of consultants and engineers. Work with customer technical leads, client executives, and partners to manage and deliver implementations of cloud solutions becoming a trusted advisor to decision-makers throughout the engagement. Interact with business, partners, and customer technical stakeholders to manage project scope, priorities, deliverables, risks/issues, and timelines for client outcomes. Work non-standard hours as needed. 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.