Microsoft Software Engineer 

Taiwan, Taoyuan City 

141878270

a strong sense

As a

Required Qualifications

• Bachelor's Degree in Computer Science, or related technical discipline with proven experience coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python,
  • OR equivalent experience.
• Experience programming in one or more of the following: SQL, SSAS, Python, Spark, or Scale.
• Experience applying analytical techniques and structured design methods to develop software solutions.

Preferred Qualifications

• Familiarity with finance data structures and business reporting rhythms.
• Exposure to Microsoft Azure or other cloud platforms (e.g., GCP, AWS).
• Understanding of AI/ML fundamentals and tools such as Azure ML, OpenAI, or data analytics workflows.
• Knowledge of version control systems (e.g., Git) and DevOps practices.
• Experience building cloud services on Microsoft Azure.
• Experience working in Agile or iterative development environments.
• Ability to clearly communicate technical concepts across cross-functional teams.

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

Microsoft will accept applications for the role until July 17, 2025.

• Designs, develops, deploys, and operates scalable cloud-based data, analytics, automation, and tooling solutions using modern data platforms and cloud services, while integrating AI capabilities such as Azure OpenAI, Cognitive Services, and ML models to enhance system intelligence and user productivity.
• Implements and maintains robust engineering practices across design, development, and release processes to ensure services are delivered accurately, safely, and efficiently. Leverages telemetry, analytics, and flighting strategies to understand customer impact and continuously improve service quality.
• Collaborates across teams to solve complex problems, working with client partner teams to deliver cohesive end-to-end experiences, providing technical feedback to product engineering partners, and applying sound engineering principles to drive innovation and service maturity.

• Leverages GitHub Copilot to auto-generate boilerplate code for data pipelines, SQL transformations, and Spark jobs, significantly reducing development time for repetitive tasks.

• Accelerates development workflows by leveraging GitHub Copilot to auto-generate boilerplate code for data pipelines, SQL transformations, and Spark jobs—reducing time spent on repetitive tasks and enabling rapid prototyping of data engineering solutions such as window functions, partitioning strategies, and schema evolution logic.
• Improves code quality and maintainability by using Copilot to enforce consistent coding patterns across ETL scripts and data models, while also generating docstrings, inline comments, and unit tests to enhance readability and test coverage.
• Fosters a culture of AI-assisted development by sharing Copilot-generated snippets and best practices with the team, promoting continuous learning and collaborative improvement.