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Principal Engineer Manager Azure Storage

Microsoft

Redmond, WAOn Site

Original Job Summary

About the Role

The Principal Engineer Manager Azure Storage at Microsoft is poised to shape the future of AI-scale storage solutions. You will lead a high-impact team focused on enhancing the storage control plane and disks platform to meet the demands of rapidly growing AI-scale workloads. This role involves driving AI-powered innovations, resolving system bottlenecks, optimizing performance and resiliency, and collaborating across organizational boundaries for platform-wide improvements.

Responsibilities

  • Collaborate with stakeholders to determine user requirements.
  • Lead teams to develop design documents and monitor dependencies.
  • Optimize, debug, refactor and reuse code for performance improvements.
  • Coordinate project plans and release plans with multiple groups.
  • Oversee product development and scaling to meet customer requirements.

Qualifications

Required: Bachelor's Degree in Computer Science or related discipline with 6+ years technical engineering experience including coding in C# or equivalent, hands-on cloud and distributed systems experience, and 2+ years as a technical lead.

Preferred: Advanced degree or additional years of experience, 4+ years people management experience, security screening compliance.

Compensation & Application

This role includes a competitive pay range (USD $139,900 - $274,800, with higher ranges in select locations) and benefits. Microsoft accepts applications until October 15th, 2025. Additional benefits and pay information are available at Microsoft Careers.

Key skills/competency

  • Distributed Systems
  • Azure Storage
  • Cloud Architecture
  • Performance Optimization
  • Scalability
  • AI-scale Workloads
  • C#
  • Leadership
  • Software Development
  • Team Collaboration

How to Get Hired at Microsoft

🎯 Tips for Getting Hired

  • Research Microsoft culture: Study mission, values, and team insights on LinkedIn.
  • Customize your resume: Tailor technical and leadership experiences.
  • Highlight distributed systems: Emphasize cloud and AI workload expertise.
  • Prepare with examples: Demonstrate successful large-scale projects.

📝 Interview Preparation Advice

Technical Preparation

Review distributed systems architecture.
Practice debugging and performance tuning.
Refresh cloud platforms and API integrations.
Study large-scale data management techniques.

Behavioral Questions

Discuss a time you led a project.
Explain conflict resolution in teams.
Detail experiences with cross-team collaboration.
Share how you handle high-pressure updates.