＜About the job＞ As the Senior Data Engineer or Data Architect, you‘ll join the various advanced Data Science & AI Projects in the corporate headquarters. As well as developing intelligent applications via related AI and Big Data Analytics Technology for digital transformation, you will have plenty of opportunities to develop emerging applications based on different use cases and expand your tech skillset in this world-class company (Fortune Global 500, 20th). ＜Job Description＞ *Type 1：Senior Data Engineer Responsible for acquiring data using API, Web scraping, or other data accessing protocol/scripting and developing the ETL data pipelines, and the data aggregation systems. Using software development experience to design and build high-performance automated systems. As below: 1. Data Processing (1)Data ETL(Extracting/Transforming/Loading) process engineering and querying from relational data management(such as SQL Script). (2)Building systematic data quality processes and checks to ensure data quality and accuracy. (3)Solid coding experience in Python or Java. 2. Data Pipeline Development (1)Develops a data integration process, including creating scalable data pipelines and building out data services/data APIs. (2)Create a data processing automation and monitoring mechanism by optimizing the data pipeline process. (3)Experience with dataflow/workflow/management tools, such as Apache Nifi, Apache Airflow, Azkaban, etc., is preferred. 3. Data Crawling (1)Build scalable tools that automate web crawling, scraping, and data aggregation from various web pages using frameworks such as Scrapy. (2)Accessing data from REST APIs, particularly in parsing data in disparate formats such as JSON and XML, and developing automated engineering. (3) (Nice to Have) Knowledge of server-based front-end/UI technologies, including Vue/React and HTML/CSS, is preferred. *Type 2：Data Architect Responsible for designing, implementing, and maintaining scalable and reusable system architectures/data architectures for complex data structures and large data in data science and AI projects. As below: 1. Data Schema Design (1)Collaborate with the team to design DB/Table Schema and Data Schema. (2)Consolidate the requirements and use data engineering tech to design and implement a robust Data Mart. (3)Experience handling all kinds of structured/semi-structured/unstructured data and streaming data is preferred. (4)Hands-on experience with Dimensional Data Modeling(Column-based data warehouse) or NoSQL Schema design. 2. Data Platform Architecture (1)Design and build data infrastructure/platform components to support complex data pipelines ingesting various data from multiple internal and external data sources and processing. (2)Familiar with Big Data frameworks and processing technologies, ex: Hadoop, Apache Spark, NoSQL ...etc. (3)Familiar with AZURE or AWS cloud data services(hands-on experience with cloud infrastructure will be a plus) (4)Familiarity with the Linux OS environment, the Shell Scripting, and infrastructure knowledge. (5)(Nice to Have)Experience with declarative infrastructure/container technologies, such as Docker and Kubernetes (k8s/k3s). (Nice to Have).資訊工程學類,數學統計學門,電算機學門

About us The AI Lab at Quanta is focused on empowering the company through AI. We develop AI algorithms and software solutions that not only enhance our products but also optimize productivity across various functions within the organization. We also provide AI information and knowledge for the executives from different business units for strategic decision-making. The lab fosters innovation, encouraging groundbreaking ideas to push the boundaries of AI and drive transformative change. Job description As a data scientist in the AI Lab, you will have the opportunity to work closely with project managers, software engineers, and other stakeholders to develop AI-powered solutions for the diverse functional teams, including engineering and manufacturing. You will have access to a remarkable computing resource (100+ GPUs and 1000+ CPU cores) enabling you to develop the models and algorithms and experiment with state-of-the-art algorithms. Responsibilities ●Execute data science and artificial intelligence projects, from project inception to completion. ●Develop and implement models or algorithms to solve engineering and manufacturing problems. ●Collaborate with project managers, software engineers and other stakeholders to develop data science and artificial intelligence solutions. ●Stay up-to-date on the latest data science and artificial intelligence trends.數學統計學門,資訊管理學類,工程學門

About us The AI Lab at Quanta is focused on empowering the company through AI. We develop AI algorithms and software solutions that not only enhance our products but also optimize productivity across various functions within the organization. We also provide AI information and knowledge for the executives from different business units for strategic decision-making. The lab fosters innovation, encouraging groundbreaking ideas to push the boundaries of AI and drive transformative change. Job description As a data science manager, you will lead and manage a team of data scientists to develop and implement AI-powered solutions for the company. You and your team will have access to a remarkable computing resource (100+ GPUs and 1000+ CPU cores) to develop the models and algorithms and experiment with state-of-the-art algorithms. Responsibilities: ●Lead and manage a team of data scientists. ●Collaborate with project managers, software engineering team and other stakeholders to develop data science and artificial intelligence solutions. ●Coordinate and manage project priorities, deadlines, and deliverables. ●Stay up-to-date on the latest data science and artificial intelligence trends.數學統計學門,資訊管理學類,工程學門

The Inventec Digital Center is a research and development facility for all things related to Digital Transformation, Data-Centric AI, and Trustworthy AI. Our primary mission is to influence and empower business and corporate units with digital knowledge constructively and collaboratively. We are responsible for implementing the digital strategy, discovering insights from the data, and executing them in the company. We are a team with a broad spectrum of talents, including project managers, data scientists, AI researchers, and software engineers. The group is a flat organization, and we frequently collaborate with colleagues outside of our center, academic consultants, and business partners outside of the company. Our members thus enjoy the unique opportunity to publish in top-tier academic venues, author technical patents, and produce real-world impacts during their career in the center. 1. Anchor the stakeholders‘ or users’ problems to conceptualize and prototype improvements with company data assets. 2. Lead technical delivery on prototype analysis pipelines including but not limited to data collection, analytical method development, and presentation. 3. Capture data-added value by discovering opportunities for new methods or applications. 4. Coordinate projects and interact with cross-functional departments to enable a data-driven culture and make company data comprehensive, approachable, and trustworthy. 數位中心為一研究與發展部門。主要負責公司數位轉型以及資料驅動／人工智慧專案／可信賴人工智慧的開發。我們與公司各單位／部門合作，從資料出發，發現資料中隱含之潛力與價值，進而提出具有建設性的建議。除了公司內部各單位／部門，數位中心也頻繁的與外界產學單位合作，其中包含國內外知名大學、企業合作夥伴。中心主要工作內容包含但不局限於數位決策、挖掘資料價值、以及系統落地與執行。中心組織結構扁平，直屬於部門主管，部門同仁多元且合作密切，涵蓋專案經理、資料科學家、人工智慧研究員、以及軟體工程師。數位中心鼓勵中心同仁將成果投稿至學術會議與期刊、技術專利並期許產出能對世界產生影響 工作內容： 1. 資料結構分析: 釐清資料定義、剖析資料特性、整合資料、資料視覺化 2. 問題的定義和判別: 發掘與分析問題，提出觀察與建議，並與團隊合作建立機器學習模型演算法 3. 研究及執行可數據驅動的解決方案: 實作並改良機器學習技術，分析並建構研發、製造、營銷、管理等數據指標 部門額外福利： 【專業延伸】定期舉辦讀書會，部門同仁自發性地講解不同的專業知識，延伸同仁的技能組。 【接軌國際】鼓勵同仁參與國際會議，定額補助國際會議的差旅支出。數學統計學門,電算機學門,電機工程學類

•Work with Data Collection Analysts to set well-defined data collection tasks for products in development. •Coordinate basic product testing including recruiting testers, booking facilities and maintaining equipment. •Conduct data collection sessions with test subjects according to established test protocols. •Accurately record, download and enter data from test sessions . •Resolve basic issues during data collection and logging. •Applies standards and procedures to accomplish tasks. •Learns how to use and apply appropriate tools as needed for this role. •Understand and comply with Garmin’s Mission, Vision, Values and Quality Policy.工程學門,資訊管理學類,資訊工程學類

【全球智慧製造】 你知道Garmin的智慧工廠嗎? 你知道火星上出現過Garmin的產品嗎? 你知道飛行員總是配戴Garmin的手錶上天空嗎? 全球智慧製造服務計畫(GSMS)透過AI、機構、電控、資料科學、IoT、大數據等技術，將智慧製造系統，即時控制與調整全球生產系統，且在地化支援亞洲、美洲、歐洲多個國家 如果你想體驗不同的文化，綻放自己的光芒！ 現在就投遞履歷，讓我們見識你的獨特潛力！ 【Introduction】 With increasing velocities, varieties and complexity of data at Process Integration (PI), the PI Data Engineering Team becomes the important role supporting existed or new projects using big data techniques to manipulate large streaming/batch dataset with various format on highly efficient way. 【Responsibilities】 -Desgin and Implement data batch/streaming pipelines on Hadoop and Spark eco-systems supporting production line -Cross-functional collaboration with domain experts and data scientists -Understand the metrics from automachines used in Garmin factory and delever the efficinet data pipelines for downstream projects 【Requirements】 -2 Years+ of programming using Scala/Java/Python -2 Years+ of experience on RDBMS like Orcale, MySQL, SQL Server about data data modeling and query performance tuning -1 Years+ of designing end to end data pipeline on distributed system like Kafka, Spark, Hadoop, etc -1 Years+ in developing Web service/Restful APIs -Be positive, data loving and interested in growing into more senior data engineer工程學門,資訊管理學類,數學統計學門

1. 利用數據分析技術(如: 訊號處理、機器學習、深度學習、統計與作業研究等但不限於)，建立設備狀態/製程品質/排程最佳化相關分析服務並實際應用於台達內外部專案上。 2. 設計、協助及管理資料分析及最佳化專案、培訓等業務推動。 3. 參與智慧製造、智慧企業等產業轉型專案，針對上述範疇內之設備/裝置共同討論與研究正確的可分析數據，並協助設計分析流程(含資料採集、邊緣運算分流、演算法選用等)。 4. 建立分析模組化/自動化(CI/CD)等相關MLOPs服務，加速分析服務落地應用。數學統計學門,電算機學門,工程學門

【全球智慧製造】 你知道Garmin的智慧工廠嗎? 你知道火星上出現過Garmin的產品嗎? 你知道飛行員總是配戴Garmin的手錶上天空嗎? 全球智慧製造服務計畫(GSMS)透過AI、機構、電控、資料科學、IoT、大數據等技術，將智慧製造系統，即時控制與調整全球生產系統，且在地化支援亞洲、美洲、歐洲多個國家 如果你想體驗不同的文化，綻放自己的光芒！ 現在就投遞履歷，讓我們見識你的獨特潛力！ 【Introduction】 Data Engineering Team is part of Garmin‘s Process Integration Department, we are looking for engineer to join our data infrastructure team. Cooperate with Data Engineer to build, maintain and optimize data platform and data pipeline. Our mission is to drive stability, scalability and efficiency for the PI data ecosystem and build a manufacturing data center in Garmin. 【Responsibilities】 1. Achieve stability of the entire data infrastructure 2. Create monitoring and alerting processes for the data infrastructure team 3. Manage access control to data infrastructure 4. Proven work ability, including implementation, operation and troubleshooting 5. Create automation tasks / self-services / documentations to reduce manual operation tasks 6. Continuously improve and evolve our data platform architecture for future challenges 【Requirements】 1. Skilled in setting up, upgrading, maintaining and monitoring data platform services such as Kafka, Hadoop HDP/CDP/Apache, ElasticSearch, Cassandra, Redis. etc 2. Experience in building up feasible and generic monitoring architecture using solutions like Prometheus/Grafana or zabbix 3. Proficient in Python or Java programming language 4. Familiar with Linux operating system and shell script 5. Hands-on experience with container (Docker composes, Docker swarm or Kubernetes) 【Bonus Points】 1. Familiar with IaC tools (Ansible) and CI/CD pipeline (Gitlab, Jenkins) 2. Experience in deploying data pipeline with NoSQL databases(Cassandra, Elasticsearch or Redis) 3. Knowledgeable in designing monitoring and alerting mechanism for data pipeline工程學門,資訊管理學類,數學統計學門

1. 以機器學習、深度學習、統計與作業研究等技術，分析內外部客戶資料，提供合適的解決方案 2. 研究與開發人工智慧之演算法、應用和服務 3. 設計、協助及管理資料分析及最佳化專案、培訓等業務推動 4. 針對台達工廠製程相關數據進行分析技術研究與開發工程學門,數學統計學門,資訊工程學類

【全球智慧製造】 你知道Garmin的智慧工廠嗎? 你知道火星上出現過Garmin的產品嗎? 你知道飛行員總是配戴Garmin的手錶上天空嗎? 全球智慧製造服務計畫(GSMS)透過AI、機構、電控、資料科學、IoT、大數據等技術，將智慧製造系統，即時控制與調整全球生產系統，且在地化支援亞洲、美洲、歐洲多個國家 如果你想體驗不同的文化，綻放自己的光芒！ 現在就投遞履歷，讓我們見識你的獨特潛力！ 【Introduction】 With increasing velocities, varieties and complexity of data at Garmin, the PI Data Engineering Team becomes the important role supporting data projects using big data techniques to manipulate large streaming/batch dataset with various format on highly efficient way. However, with the substantial amount of data at Garmin, we have embarked on efforts to enhance the quality and standards of our data, aiming to unlock the true value of data. As a PI Data Governance Specialist, we sincerely invite you to participate in various aspects of the data governance project, including the selection of diverse DG tools, conducting PoCs, and formulating processes, all aimed at achieving a significant improvement in Garmin‘s data quality. 【Responsibilities】 -Develop and implement data governance standards, frameworks, workflows, and tools to enhance the data value at Garmin. -Assist the team in promoting awareness of Data Governance by providing internal consulting and training support. 【Requirements】 -Experienced in working on Data Governance-related projects. -Familiar with at least one programming language, such as Python, Java, or Scala -Knowledgeable in Data Modeling, including 3NF and Dimensional designs for OLTP and OLAP usage. 【Preferences】 -Prior experience in launching and introducing data governance from inception to implementation (including process flow and tools) is a significant advantage. -Prior experience in MDM (Master Data Management) and Data Mesh projects is an advantage -Experience in integrating Data Governance projects and solutions with Data Platforms.工程學門,資訊管理學類,數學統計學門

＜About the job＞ As the AI System Analyst, you‘ll join the various advanced Data Science & AI Projects in the corporate headquarters. As well as developing intelligent applications via related AI and Big Data Analytics Technology for digital transformation, you will have plenty of opportunities to develop emerging applications based on different use cases and expand your tech skillset in this world-class company (Fortune Global 500, 20th). ＜Job Description＞ Responsible for gathering and analyzing the requirements and contributing to designing, developing, testing, and deploying in all phases of the AI system development project lifecycle, as below： 1. Collaborate with business data analysts to analyze user requirements and ensure that requirements and acceptance criteria satisfy user needs. 2. Create a system requirement specification to elaborate on system design, system components/interfaces, and data schema. 3. Work with the multi-functional engineering team(e.g., data scientist, AI/ML engineer, data engineer, AI software engineer..., etc.) to ensure technical feasibility. 4. Drive usability and quality of the AI system developed and ensure all system requirements are well implemented. 5. Work on various enterprise AI system applications and problems, and analyze issues to identify root causes and prevention. 6. Create the Wireframes(or UI Prototypes) for AI system feature discussion with users and provide them to the UI/UX design team. 7. Author and update internal documentation; initiate and deliver requirement specification and system analysis/system design documentation. ＜Required Skills＞ 1. Practical experience in requirements gathering and analysis and change management 2. Experience co-working with front-end and back-end system development teams. 3. Strong analytical, verbal, and written communication, teamwork, and highly collaborative skills. 4. Experience with Microsoft Visio, Axure RP(or other wireframe tools). 5. Practical experience in Relational DB (e.g., MS SQL, PostgreSQL) and ability to write SQL queries. 6. Mastery of Microsoft Office programs (Word, Excel, PowerPoint) (Nice to have, but not necessary) 1. Mastery of QA methodology and problem-solving tools/techniques in software engineering. 2. Knowledge of AI/Data Science Tech(e.g., Machine Learning, Deep Learning, Statistics, Quantitative modeling techniques). 3. Knowledge of Big Data Engineering(Hadoop Ecosystem). 4. Knowledge of Data Warehouse and Dimensional Data Modeling.資訊工程學類,資訊管理學類,其他數學及統計學類

＜About the job＞ As the AI Software Engineer, you‘ll join the various advanced Data Science & AI Projects in the corporate headquarters. As well as developing intelligent applications via related AI and Big Data Analytics Technology for digital transformation, you will have plenty of opportunities to develop emerging applications based on different use cases and expand your tech skillset in this world-class company (Fortune Global 500, 20th). ＜Job Description＞ Responsible for deploying the AI/Data Science collaborative framework and building the AI model and data operating infrastructure. Using software development experience to design and develop high-performance automated systems for AI development and operation. As below: ．Collaborating with Data Scientist/AI ML Engineer team, other software system development teams, and the infrastructure team. ．Ability to utilize various tools/methods to build the MLOps/DataOps/DevOps and deploy and manage the AI Development framework and infrastructure ．Developing infrastructures for data transformation and ingestion and automating important infrastructure to process data ．Deploy AI models to the Inference server and optimize the performance of the model serving operation reliably and efficiently. ．Assist the Data Scientist/AI ML Engineer team in converting the AI models into APIs to serve other systems or integrate with other systems. ＜Skill Sets＞ (1)Excellent problem-solving and troubleshooting skills. (2)Genuine passion for learning new technologies and open-source projects. (3)Familiarity with Python and Java (python is a must) (4)Good understanding of the Linux OS environment, the Shell Scripting, and infrastructure/networking knowledge. (5)Experience with GitLab CI/CD (Nice to have but not necessary) (1)Experience with MLops and Model Serving tools. (2)Experience in GPU programming and performance tuning (3)Being familiar with AZURE (or AWS) cloud infrastructure will be a plus (4)Familiar with declarative infrastructure/container technologies, such as Docker and Kubernetes (k8s/k3s)資訊工程學類,資訊管理學類,其他數學及統計學類

1. Utilizing technologies such as machine learning, deep learning, statistics, and operations research to analyze internal and external customer data and provide suitable solutions. 2. Researching and developing algorithms, applications, and services for AI technology to achieve predictive maintenance of smart machines. 3. Co-work with smart machine developers to optimize the performance of smart machines before deployment. 4. Conducting technical research and development on data analysis for Delta smart factory processes.資訊工程學類,工程學門

參與公司重大策略專案，執行數據分析並提出有效之成果。 1.精通數據分析及使用Python，熟悉多種方法論，可提出過往執行資料分析的方法論及成果。 2.具管理經驗，溝通協調能力佳，可針對分析案件提出時程及工作分派，並有效管制作業時程。 3.可接受快節奏之工作步調、可適應同時負責多項專案之壓力。 4.具備製造業經驗，鋼鐵相關產業尤佳。數學統計學門,資訊工程學類,資訊管理學類

【全球智慧製造】 你知道Garmin的智慧工廠嗎? 你知道火星上出現過Garmin的產品嗎? 你知道飛行員總是配戴Garmin的手錶上天空嗎? 全球智慧製造服務計畫(GSMS)透過AI、機構、電控、資料科學、IoT、大數據等技術，將智慧製造系統，即時控制與調整全球生產系統，且在地化支援亞洲、美洲、歐洲多個國家 如果你想體驗不同的文化，綻放自己的光芒！ 現在就投遞履歷，讓我們見識你的獨特潛力！ 【介紹】 數位轉型和資料科學是提高工廠運營效率和效益的關鍵。我們正在尋找一位熱衷於數位轉型且具備資料科學專業知識的夥伴，協助我們實現目標。 【必要條件】 熱情： 對數位轉型和資料科學領域持有積極的學習態度，能夠接受挑戰並不斷尋求創新的方法來改進工廠運營，不斷提升專業知識和技能。 專業知識： 具備資料科學和分析的專業知識，包括數據處理、機器學習和預測性分析等方面的技能，能夠從複雜的數據中識別關鍵洞見，提出可操作的解決方案。 合作能力： 能夠有效地與不同部門合作，協調專案的進行。 【工作內容】 1.使用資料科學技巧，分析大量數據以尋找工廠運營的關鍵洞見 2.依據生產目標定義問題、收集資料、分析以及開發演算法以提升整體生產效益 3.協助設計和實施工廠數位轉型計劃，包括評估現有流程和技術，提供改善建議 4.協助管理層制定基於數據分析的決策，並追蹤實施結果 5.使用資料視覺化工具提供引人入勝的報告和儀表板，清晰展示數據洞見工程學門,數學統計學門,資訊科學學門

「台達研究院」(Delta Research Center, DRC)成立於2013年，為台達集團總部研發單位，除致力於大數據分析及物聯網應用與解決方案的開發與整合，加速企業轉型成功，也積極與產官學研生態體系協作，以開放創新模式，創造多贏生態圈。2022年台達研究院進入下一階段，專注於研發台達下下世代(next-next-generation)產品或解決方案之前瞻技術。 在「台達研究院」之下，團隊專注在模擬最佳化、機器人演算法、數位孿生建模與應用，發展具商業價值的AI應用與解決方案。 本職缺主要工作內容: 1. 以機器學習、深度學習、統計與作業研究等技術，分析內外部客戶資料，提供合適的解決方案 2. 研究與開發人工智慧之演算法、應用和服務 3. 設計、協助及管理資料分析及最佳化專案、培訓等業務推動 4. 參與Smart Design, Smart Manufacturing/智慧製造, 節能最佳化等產業轉型專案。 你/妳將會應用資料分析技術於以下四個類別的問題 1. Video & Image Processing and Analytics □ 品質檢測 □ 視覺定位 □ 姿態辨識 2. Natural Language Processing and Knowledge Engineering □ 語意理解 □ 大型語言模型應用 □ 設計文件知識萃取 3. Time Series Analysis □ 設備機台數據分析 □ 電源產品數據分析 □ 節能數據分析 4. Operations Research □ 智能調機、路徑規劃、參數最佳化 □ 產能提升、工廠配置、物流優化 □ 產品設計優化數學統計學門,電算機學門,工程學門

「台達研究院」(Delta Research Center, DRC)成立於2013年，為台達集團總部研發單位，除致力於大數據分析及物聯網應用與解決方案的開發與整合，加速企業轉型成功，也積極與產官學研生態體系協作，以開放創新模式，創造多贏生態圈。2022年台達研究院進入下一階段，專注於研發台達下下世代(next-next-generation)產品或解決方案之前瞻技術。 在「台達研究院」之下，團隊專注在模擬最佳化、機器人演算法、數位孿生建模與應用，發展具商業價值的AI應用與解決方案。 本職缺主要工作內容: 1. 以機器學習、深度學習、統計與作業研究等技術，分析內外部客戶資料，提供合適的解決方案 2. 研究與開發人工智慧之演算法、應用和服務 3. 設計、協助及管理資料分析及最佳化專案、培訓等業務推動 4. 參與Smart Design, Smart Manufacturing/智慧製造, 節能最佳化等產業轉型專案。 你/妳將會應用資料分析技術於以下四個類別的問題 1. Video & Image Processing and Analytics □ 品質檢測 □ 視覺定位 □ 姿態辨識 2. Natural Language Processing and Knowledge Engineering □ 語意理解 □ 大型語言模型應用 □ 設計文件知識萃取 3. Time Series Analysis □ 設備機台數據分析 □ 電源產品數據分析 □ 節能數據分析 4. Operations Research □ 智能調機、路徑規劃、參數最佳化 □ 產能提升、工廠配置、物流優化 □ 產品設計優化數學統計學門,電算機學門,工程學門

Job Summary/Role: The Big data developer team works closely with the manufacturing functions in all relative data fields, such as, 1) connecting and automating the data pipeline from MFG file servers, API, RDB, etc., 2) building structurally data warehouse and data market for flexible application or dashboard, and 3) also handling data cleansing and data governance. In order to accelerate the development of application/analysis, Big data developer will be the individual contributor with strong experience in the technologies of Big Data, Data warehouse, SQL and NoSQL etc. Also Big data developer will also work closely with data analysts/data scientists to solve the real MFG cases. Responsibility: • Collaborate with users, data analysts, data scientists to develop flowcharts, layouts and documents to identify solutions. • Architect on real MFG needs and translate requirements into technical needs. • Identify and understand the data sources that are relevant for analysis, and implement efficient data engineering functions (including data ingestion, cleaning, ETL, integration, etc.) • Consolidate the requirements and using data engineering skills to design a robust Data Mart. • Participate in design, architecture review and deployment of Big data and data warehouse solutions. • Design for automation and monitoring mechanism in a continuous integration environment. • Bring new data technology with POC to solve existing data challenges. • With high performance and comprehensive SQL to process data in relational databases (or Map/Reduce style querying for NoSQL databases). • Work closely with user/IT/data science team to design and develop scalable data pipeline or end-to-end analytical workflow. • Provide direction, training, and guidance to less experienced team members.資訊管理學類,電機工程學類,電子工程學類

Server-Side Development: Design, develop, and maintain server-side applications and APIs that support the functionality and data exchange for web and mobile applications. • Database Management: Architect and manage databases, including designing schemas, optimizing queries, and ensuring data integrity for efficient data storage and retrieval. • Scalability and Performance: Implement strategies to ensure the scalability, reliability, and performance of backend systems to handle increasing user loads and traffic. • API Integration: Collaborate with frontend and mobile developers to define API specifications, ensuring smooth integration and data exchange between different components. • Security: Implement security best practices, including data encryption, user authentication, and access controls, to protect sensitive data and prevent unauthorized access.

Prepares monthly statements by collecting and assembling data; analyzing and investigating variances; summarizing data, information, and trends.會計學類,財務金融學類