Microsoft Principal Data Engineering Manager 

Taiwan, Taoyuan City 

721316658

Required/Minimum Qualifications

• Master'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 OR Bachelor's Degree in Computer Science, Math, Software Engineering, Computer Engineering, or related field AND 6+ years experience in business analytics, data science, software development, data modeling, or data engineering OR equivalent experience.
• 6+ years of experience in data engineering, software development, or technical program management.
• 3+ years of experience managing cross-functional or cross-team projects, building partnerships with internal/external clients and delivering high-quality data solutions.
• 4+ experience with big data platforms, data modeling, extract, transform and load (ETL), and cloud technologies (Microsoft Fabric, Azure Data stack, Lakehouse architectures).

Additional or Preferred Qualifications

• Master's Degree in Computer Science, Math, Software Engineering, Computer Engineering, or related field AND 8+ years 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 12+ years experience in business analytics, data science, software development, data modeling, or data engineering OR equivalent experience.
• 3+ years people management experience.
• 3+ years experience with data governance, data compliance and/or data security.
• Experience in digital media, paid media, marketing, or web analytics.
• Experience with secure development practices, privacy compliance, and Role-Based Access Control (RBAC) security models.
• Experience managing execution through vendor teams.

Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here:Microsoft will accept applications for the role until October 23, 2025.

Team Leadership & Development

• Lead, coach, and empower a team of data engineers to deliver high-impact data solutions.
• Foster a culture of innovation, accountability, and customer focus.
• Model Microsoft values and drive team growth through mentorship and career development.

Technical Strategy & Execution

• Define, document and drive development of connected marketing data model across the customer lifecycle identifying data gaps in the current state and producing strategy and roadmap to address the gaps.
• Identify patterns of data needs to help translate to data product capabilities and solutions.
• Own the end-to-end delivery of data products and models that enable critical business insights and campaign performance measurement.
• Provide technical leadership by identifying dependencies across teams and translating product vision and strategy into tangible impact.
• Define and drive technical requirements, architecture, and roadmaps for scalable data solutions using Microsoft Fabric, Azure Data stack, and Lakehouse architectures.
• Oversee data acquisition, semantic model development, and deployment pipelines.

Stakeholder Management

• Build partnerships with analytics, marketing, and engineering stakeholders to understand business needs and evaluate solution options.
• Influence and negotiate cross-organizational dependencies impacting roadmaps and delivery.
• Drive the federated marketing data strategy across multiple source data engineering teams.

Operational Excellence

• Ensure data quality, reliability, and security across all data flows and products.
• Implement monitoring, issue responsiveness, and privacy-compliant data processing practices in collaboration with Data Platform and Product Management teams.
• Drive Agile/Scrum execution, backlog management, and vendor team coordination.

Innovation & Continuous Improvement

• Define and establish engineering excellence frameworks, standards, and best practices, driving adoption across Data Engineering.
• Contribute to enhancing architecture, design principles, and frameworks through feedback and domain-specific scenarios.
• Champion the adoption of innovative technologies and continuous improvement across the data engineering organization.

Other

• Embody our and