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【關於我們 - Data Munger AI】 Data Munger 致力成為企業與實用 AI 解決方案間的最佳夥伴，從導入一路陪伴到落地。 在人人喊AI的時代下，真正為企業打造一個會持續進化的「AI 大腦」讓決策更快、流程更簡，讓人力價值最大化。 官網： https://datamunger.io/ 💼 工作職責 資料處理管道設計與開發 使用 Python 與 BigQuery SQL 為 AI 應用設計、開發及維護資料處理流程，確保機器學習模型可獲取高品質資料。ETL/ELT 工作流程構建 建立並優化 ETL/ELT 流程，確保資料自動化處理與數據一致性。RAG 系統實作 應用 RAG（檢索增強生成）技術，提升 AI 互動的準確性與上下文相關性。向量資料庫與查詢優化 優化向量資料庫（如 Pinecone、Qdrant）及 SQL/BigQuery 查詢效能，提升 AI 搜尋與回應速度。API 建構與維護 使用 Python 框架（FastAPI、Flask）建立並維護資料處理與 AI 服務 API。機器學習模型與資料管道部署 在雲端基礎架構（主要以 GCP 為主，並整合部分 AWS）上部署 ML 模型與資料管道，實踐 MLOps 原則以確保部署具備可重現性、擴展性及監控能力。跨部門協作與技術創新 與資料科學家、AI 研究人員及前端團隊協作，共同打造端對端 AI 產品，並持續導入最新技術以優化解決方案。

We are looking for a pragmatic and proactive Cloud Data Engineer to join our core data team. In this role, you will be responsible for the critical task of consuming tracking data from the webshop and transforming it for the Business Intelligence (BI) Core Warehouse. This is a high-impact position. You will work with a modern tech stack on the Google Cloud Platform to ensure our data pipelines are robust, scalable, and capable of handling high volumes of traffic. If you are an advanced Python developer who loves Infrastructure as Code and thrives in a dynamic environment, we want to hear from you. Key Responsibilities Pipeline Development: Design, build, and maintain scalable streaming data pipelines using Apache Beam (Dataflow) and Python.Infrastructure as Code: Take ownership of our cloud infrastructure using Terraform (Advanced level) to manage resources on Google Cloud Platform.Orchestration: Manage and optimize complex data workflows using Apache Airflow (Cloud Composer).Reliability Monitoring: Ensure the stability of high-importance products. Implement monitoring solutions using Grafana to keep a pulse on system health.CI/CD: Maintain and improve CI/CD pipelines using GitHub Actions to ensure smooth and reliable deployments.Collaboration: Work independently on tasks while communicating effectively with the team to integrate solutions into the wider ecosystem (BigQuery, Snowflake).

About The Role The Data Engineer is responsible for managing the StraitsX’s data pipeline that underlie all our ETL/ELT process and data warehouse solutions. The teams’ mission is to achieve maximum efficiency and stability of the entire data infrastructure.What Will You Do As a Data Engineer, you will work to ensure the smooth running of all our data pipelines, and that accurate data is available in a timely manner for management to make informed decisions and operational teams to track their metrics. The responsibilities include: Develop and maintain data pipeline and infrastructure for ETL/ELT process, Data Warehouse, Business Intelligence reporting.Create active and passive monitoring for data infrastructure (alerts, usage dashboards, etc).Manage access control to data infrastructure.

【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！

主要職責： 1.設計並實現高可用性、可擴展且安全的Google Cloud Platform雲端架構，確保符合客戶業務需求與技術要求 2.評估現有系統架構，提供最佳化方案與雲端遷移策略 3.建立與管理核心GCP服務，包括Compute Engine、App Engine、Cloud Functions等運算服務與VPC、Cloud Interconnect、Cloud Armor等網路服務 4.設計與實施資料庫解決方案，熟悉Cloud SQL、Cloud Spanner、Firestore、BigQuery等服務的部署與最佳化 5.實施基礎設施即代碼(IaC)策略，使用Deployment Manager、Terraform等工具自動化部署流程 6.建立全面的監控與告警機制，運用Cloud Monitoring、Cloud Logging確保系統效能與安全合規，並進行故障排除與效能優化 7.設計與實施AI/ML解決方案，包括使用Vertex AI、Gemini API、Vision AI等GCP AI服務，協助客戶將AI功能整合至其應用程式與業務流程 8.開發與部署機器學習模型，使用AutoML、BigQuery ML等工具，並建立模型監控與管理流程 9.協助客戶解決技術問題，提供諮詢與支援，作為客戶與技術團隊間的溝通橋樑 10.持續關注GCP新服務與最佳實踐，不斷改進架構設計

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."

This role requires you to work in a shift pattern or non-standard work hours as required. This may include weekend work.Minimum qualifications: Bachelor’s degree in Science, Technology, Engineering, Mathematics, or equivalent practical experience. 5 years of experience with two or more of the following: web tech, data/big data, SQL, BigQuery, systems admin, machine learning, networking, Kubernetes, Oracle, or SAP. Experience with coding in a general purpose coding language (e.g., Java, C, C++, Python, Shell, Go, JavaScript, etc.) and in virtualization and orchestration frameworks. Experience with Linux/Unix or other operating systems (e.g., Kernel to Shell, file systems, client-server protocols, etc.). Preferred qualifications: Experience with debugging, working on distributed applications or micro-services in a cloud based environment (e.g., Docker, Kubernetes, etc.). Experience in data analytics, warehousing, Extract, Transform, and Load (ETL) development, data science, or other big data applications. Experience with SQL database administration, open source software communities, cloud networking solutions, or distributed computing. Experience working in a changing organization with extensive cross-collaboration across functions. Experience in technical consulting on database design and architecture supporting large enterprise customers with high Service Level Objective (SLO) and Service Level Agreement (SLA) requirements. 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. In this role, you will own the customer issues in addition to providing level two support to the other support teams. You will be a part of a global team that provides support to help customers make the switch to Google Cloud. You will troubleshoot technical problems for customers with a mix of debugging, networking, system administration, updating documentation, and when needed, coding/scripting. You will make our products easier to adopt and use by making improvements to the product, tools, processes and documentation.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 Develop an in-depth understanding of Google Cloud's data analytics (e.g., BigQuery) and underlying architectures by troubleshooting, reproducing, and determining the root cause for customer-reported issues, building tools, and faster diagnosis. Act as consultant and subject matter expert for internal stakeholders in engineering, business, and customer organizations to resolve technical deployment obstacles and improve Google Cloud. Work as part of a team of engineers and consultants that globally ensure 24-hour customer support. Understand customer issues, advocate for their needs with internal teams, including product and engineering teams, and drive high-quality production. Work with customers on their production databases. 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.

Mô tả công việcCreate, maintain, and update test-related artifacts, including Test Cases, Test Plans, and Test Reports for marketing products.Perform testing on advertising features such as:Campaign, Creative, Ad Group managementTargeting, Budgeting, Bidding logicTracking (Impression, Click, Conversion)Ads Reporting DashboardExecute all phases of testing:Functional Testing, Integration Testing (Ads services, tracking, billing, reporting),System Testing and Regression Testing, Ad-hoc Testing for risk-based scenarios in production-like environments.Track testing progress, monitor product quality, and report issues/risks to TL/PM in a timely manner.Analyze Ads/promotion business requirements and participate in requirement/PRD reviews to detect logic gaps and tracking/data issues early.Prepare test data and test environments for Ads campaigns, creatives, budgets, and reports.Analyze defects, identify root causes, and propose solutions to improve Ads/promotion system quality and performance.Collaborate closely with Developers, Product, Data, and Operations teams to ensure quality, SLA, and stability of the Ads/promotion platform.Contribute to improving QC processes, checklists, and test strategies for Ads/promotion systemsYêu cầu công việcExperience Technical SkillsBachelor’s degree in Computer Science or related fields.At least 2 - 3 years of experience in Manual Testing for Web, Mobile, and Backend systems.Hands-on experience in:Integration Testing, creating Test Cases and Test Plans across multiple projects.API Testing using Postman (request/response validation, tracking events).Database querying (MySQL, PostgreSQL, BigQuery, etc.).Knowledge of: Software Development Methodologies (Agile/Scrum).Soft SkillsStrong analytical mindset with attention to data accuracy and business logic.Ability to handle multiple projects and work under tight release schedules.Proactive, responsible, and a strong team player.Willingness to work overtime when required by project needs.Nice to HaveExperience in Test Automation for Web, Mobile, or Backend systems.Experience in testing: Ads Platform / AdTech / Tracking or Data-intensive systems is a strong advantage.

The MoMo Recommendation Platform is a complex system that powers personalized experiences for millions of users using a diverse range of technologies.We’re looking for a Senior Software Engineer with strong system thinking, architecture design skills, and a product mindset to help build the MLOps platform that transforms any AI/ML solutions into production-grade systems at scale.Mô tả công việcThink like a product engineer: you don’t just “code a solution” – you build a platform that empowers others to deliver intelligent sysDesign and develop a flexible platform that turns AI/ML solutions into production-ready systems: microservices, batch pipelines, or real-time APIsBuild infrastructure to support:Model training pipelinesPackaging deploymentServing rolloutMonitoring alertingCollaborate closely with Data Scientists, Business, and Product teams to deeply understand requirements and design adaptable, scalable solutionsIntegrate platform components into MoMo’s broader infrastructure: promotion engine, A/B testing, analytics, real-time scoring, etc.Yêu cầu công việcMust-Have5+ years of experience in software development, system architecture, or backend/platform engineeringProficiency in one or more of the following: Python, Bash, C++, JavaScript, Java, or GoStrong problem-solving skills and teamwork spiritExperience with:Platform Deployment: Kubernetes, Helm, Argo CD, Argo Rollouts, Docker, Google Cloud Platform (GCP) or Amazon Web Services (AWS)Serving APIs: FastAPI, gRPC, MLflow, KServe, custom logic services, REST APIsData Messaging: BigQuery, Redis, MongoDB, PostgreSQL, Oracle, MySQL, Kafka, Pub/SubOrchestration Workflow: Airflow, Argo WorkflowsCI/CD Monitoring: GitHub Actions, Prometheus, GrafanaData Sources: App event streams, relational databases, messaging systems, APIsSolid understanding of distributed systems and cloud-native architectureAbility to design systems that support diverse solution typesPlatform mindset: you build for stability, scalability, and long-term maintainabilityStrong communication and collaboration skills – able to work cross-functionally with Data Scientists, DevOps, and Product teamsNice-to-HaveExperience working with both AI/MLExperience scaling low-latency / real-time systemsFamiliarity with A/B testing, canary release, and shadow deployment strategiesProduct-oriented mindset: you build systems that others can easily adopt and extend

As a Senior Data Analyst in the Financial Services sector, with a focus on credit products, you will leverage your expertise in data analysis to deliver actionable insights that drive business decisions.You will be responsible for analyzing large datasets, creating financial models, and working closely with cross-functional teams to optimize credit risk strategies, customer acquisition, retention, and profitability.Mô tả công việcConduct rigorous hypothesis testing, including A/B testing, to evaluate the effectiveness of marketing campaigns and product featuresCollect, analyze, and interpret large datasets to identify trends, patterns, and insights that contribute to business growth and operational efficiency.Leading complex data analysis projects from inception to completion.Mentoring junior team members and providing guidance on technical and analytical skills.Assist in creating business cases with detailed analysis, outlining problems, opportunities, solutions, strategic directions, and performance management for investment and insurance productsPlan, forecast and monitor performance and budget of said projects while proposing necessary changes to maximize efficiencyYêu cầu công việcMinimum Qualifications (education): Bachelor's degree in a quantitative field such as Statistics, Mathematics, Economics, or Computer Science.Experience:At least 3 years of experience in data analytics, preferably in the financial services, credit sector.Experience working with digital lending productEssential skills:Experience with BI/analytics tools (Google BigQuery, Data Studio..)Proficiency in SQL, Python is a mustFamiliarity with machine learning techniques and financial modeling.Advanced proficiency in statistical analysis, and data visualization.Ability to lead and mentor junior team members.Excellent communication and presentation skills, with the ability to convey complex technical concepts to non-technical stakeholders.Strong project management skills and ability to prioritize and manage multiple tasks simultaneously.Personal characteristics:Result-orientedDo whatever it takes to get the job doneCuriosity and eagerness to learn new techniques and toolsInnovative thinking and problem-solving mindsetAttention to detail and commitment to producing high-quality work