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Microsoft Senior Data Engineer Taiwan, Taoyuan City 849641269
16.10.2025
Join M365 AI Experiences Data Platform to build the privacy first, experimentation driven data intelligence platform powering M365 Agents, People Experiences, and Windows Companions Apps. As we launch new capabilities across the ecosystem, you’ll turn raw, privacy safe signals into unified telemetry and actionable insights that let us ship faster through continuous experimentation, helping millions accomplish more every day. From industry leading “eyes off” analytics and deep behavioral understanding to mapping cross app workflows and measuring real productivity gains, you’ll architect the end to end foundation that product teams use to learn fast, decide with confidence, and build better. If you’re obsessed with software craftsmanship and responsible innovation at massive scale, come shape how M365 understands its users, and convert that understanding into intuitive, high value experiences from first instrument to final decision.
As a
Senior Data Engineer, you will design and deliver scalable, secure, and high-performance data solutions that power intelligent experiences across our ecosystem. This role sits at the intersection of software engineering and data innovation, requiring deep expertise in distributed systems, data modeling, and modern data processing frameworks. You will own the architecture and implementation of end-to-end data pipelines, ensuring reliability, observability, and compliance at scale.
Senior Data Engineer, you will design and deliver scalable, secure, and high-performance data solutions that power intelligent experiences across our ecosystem. This role sits at the intersection of software engineering and data innovation, requiring deep expertise in distributed systems, data modeling, and modern data processing frameworks. You will own the architecture and implementation of end-to-end data pipelines, ensuring reliability, observability, and compliance at scale.
In this role, you will build robust data workflows leveraging technologies such as Azure Data Factory, Synapse, Microsoft Fabric, and Spark. You’ll implement advanced transformation logic using SQL, Python, SCOPE or KQL, optimize for performance and cost, and integrate CI/CD practices for automated testing and deployment across multiple cloud environments. Beyond pipeline development, you will champion DataOps best practices, establish monitoring and alerting systems, and lead root-cause analysis to drive continuous improvement in reliability and efficiency.
Required Qualifications:
- Master's Degree in Computer Science, Math, Software Engineering, Computer Engineering, or related field AND experience in business analytics, data science, software development, data modeling, or data engineering
- OR Bachelor's Degree in Computer Science, Math, Software Engineering, Computer Engineering, or related field experience in business analytics, data science, software development, data modeling, or data engineering
- OR equivalent experience.
- Customer-facing, project-delivery experience, professional services, and/or consulting experience.
Other Requirements
Ability to meet Microsoft, customer and/or government security screening requirements are required for this role. These requirements include but are not limited to the following specialized security screenings:
- : This position will be required to pass the Microsoft Cloud background check upon hire/transfer and every two years thereafter.
Preferred Qualifications:
- Master's Degree in Computer Science, Math, Software Engineering, Computer Engineering, or related field AND experience in business analytics, data science, software development, data modeling, or data engineering
- OR Bachelor's Degree in Computer Science, Math, Software Engineering, Computer Engineering, or related field AND experience in business analytics, data science, software development, data modeling, or data engineering
- OR equivalent experience.
Responsibilities
- Design, implement, and maintain end-to-end data pipelines using Azure Data Factory (ADF), Microsoft Synapse, Microsoft Fabric, and Spark.
- Develop scalable data transformation logic using Structured Query Language (SQL), Python, and Structured Computations Optimized for Parallel Execution (SCOPE) for large-scale datasets.
- Automate orchestration, scheduling, and dependency management with built-in retry and recovery mechanisms.
- Integrate Continuous Integration and Continuous Deployment (CI/CD) pipelines for automated testing, performance validation, and multi-cloud deployments.
- Implement comprehensive observability, including logging, tracing, and real-time monitoring dashboards for data workflows and platform services.
- Design logical and physical data models, enforce schema standards, and ensure data quality, security, and compliance across structured and semi-structured data.
- Collaborate with analytics, product, and machine learning teams to deliver high-quality, scalable solutions and mentor peers in data engineering best practices.
- Define and evolve schemas for structured and semi-structured data (e.g., Structured Streams, Parquet, Delta Lake, JSON).
- Implement dimensional modeling (star/snowflake) for analytical workloads.
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