Microsoft Data Engineer 

Taiwan, Taoyuan City 

673805065

. This is a world of, more innovation, more openness, and the skya cloud-enabled world.

the operating system and provides

We work withvery largeand fast arriving data and transform it into trustworthy insightsWe build and manage pipelines, transformation, platforms, models, and so much more that empowers the Fabric product, and Cloud SystemsYou will be working alongside other Engineers, Scientists, Product, Architecture, and Visionaries bringing forth the next generation of data democratization products.to build the Future of Big Data, Data Insights and become Full Stack Data Professionals.new ideasand promote out of the box thinking when addressing complex, architecture, or technology challenges.

better served

Qualifications

• Bachelor's Degree in Computer Science, Math, Software Engineering, Computer Engineering, or related field AND 3+ years' experience in business analytics, data science, software development, data modeling or data engineering worko OR Master's Degree in Computer Science, Math, Software Engineering, Computer Engineering, or related field AND 2+ years' experience in business analytics, data science, software development, or data engineering worko OR equivalent experience.• 2+ years of experience in software or data engineering, with proven• 2+ years in one scripting language for data retrieval and manipulation (e.g., SQL or KQL).• 2+ years of experience with ETL and data cloud computing technologies, including Azure Data Lake, Azure Data Factory, Azure Synapse, Azure Logic Apps, Azure Functions, Azure Data Explorer, and Power BI or equivalent platforms.

Other Requirements

to meet Microsoft, customer and/or government security screening requirementsfor this role. These requirements include, but are not limited to the following specialized security screenings: Microsoft Cloud Background Check:

• This position will berequiredto pass the Microsoft Cloud background check upon hire/transfer and every two years thereafter.

Preferred/Additional Qualifications

• Bachelor's Degree in Computer Science, Math, Software Engineering, Computer Engineering, or related field AND 4+ years' experience in business analytics, data science, software development, data modeling or data engineering worko OR Master's Degree in Computer Science, Math, Software Engineering, Computer Engineering, or related field AND 3+ years of business analytics, data science, software development, data modeling or data engineering work experienceo OR equivalent experience.• 1+ years ofcomply withregulatory standards.• 1+ years of experience in, covering the entire machine learning lifecycle: data ingestion, preprocessing, model training, validation, deployment, and monitoring.

• You will develop anddata pipelines, including solutions for data collection, management, transformation, and usage, ensuringdata ingestion and readiness for downstream analysis, visualization, and AI model training.• You will design and implement end-to-end software life cycles, encompassing design, development, CI/CD, service reliability, recoverability, and participation in agile development practices, including on-call rotation.• You will write code to implement performance monitoring protocols across data pipelines, building visualizations and aggregations topipeline health.also implement solutions and self-healing processes that minimize points of failure across multiple product features.• You willdata governance needs, designing data modeling and handling procedures to ensure compliance with all applicable laws and policies.• You will implement and enforce security and access control measures to protect sensitive resources and data.• You will Perform database administration tasks, including maintenance, and performance monitoring.• You will collaborate with Product Managers, Data and Applied Scientists, Software and Quality Engineers, and other stakeholders to understand data requirements and deliver phased solutions that meet test and quality programs data needs, and support AI model training and inference.

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