Microsoft Data Engineer 

Taiwan, Taoyuan City 

987995649

Required/Minimum Qualifications

• Bachelor's Degree in Computer Science, Math, Software Engineering, Computer Engineering, or related field AND 2+ years' experience in business analytics, data science, data modeling or data engineering work
• OR Master's Degree in Computer Science, Math, Software Engineering, Computer Engineering, or related field
• OR equivalent experience.
• 2+ years of experience in data engineering with proven coding and debugging skills inC#.
• 2+ years of experience in writing queries usingSQL, KQL, Scope script.
• 2+ years and experience with data cloud computing technologies such as –Azure Synapse, Azure Data Factory, SQL, Azure Data Explorer, Power BI.

Additional Or Preferred Qualifications

• 5+ years of experience in data engineering with proven coding and debugging skills inC#.
• 5+ years of experience in developing solutions withMicrosoft Power Platform, includingPower BI, andPower Automate.
• Experience with extracting and handling data withREST APIs, messaging and event technologies.
• Dedication to writing clean, maintainable, and well-documented code with a focus on application quality, performance, scalability and security.
• Experience building and optimizing large-scale data processing, integration and storage.
• Analytical skills with a systematic and structured approach to software and data design.
• Problem solving, design, and implementation skills

Data Engineering IC3 - The typical base pay range for this role across the U.S. is USD $98,300 - $193,200 per year.

Data Engineering IC4 - The typical base pay range for this role across the U.S. is USD $117,200 - $229,200 per year.

Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here:

• Implement scalable and performant data models, data pipelines, data storage, management, batch ingestion and transformation solutions for real-time decisioning, reporting, data collecting, and related functions.
• Develop application components and services to support data related processes, presentation, and consumption.
• Troubleshoot and resolve issues related to data processing and storage.
• Contributes to efforts to break down larger work items into smaller work items and provides estimation.
• Remains current in skills by investing time and effort into staying abreast of latest technologies.
• Considers testability, monitoring, reliability, performance and maintainability to develop solutions for quality validation and continuous improvement.
• Use large data sets to provide insight into business and functional issues while improving data reliability, efficiency, and quality.
• Embody our