Member of Technical Staff - Principal Data Infrastructure Engineer

Overview

As Microsoft continues to push the boundaries of AI, we are on the lookout for passionate individuals to work with us on the most interesting and challenging AI questions of our time. Our vision is bold and broad - to build systems that have true artificial intelligence across agents, applications, services, and infrastructure. It's also inclusive: we aim to make AI accessible to all - consumers, businesses, developers - so that everyone can realize its benefits.

We're looking for a Member of Technical Staff - Principal Data Infrastructure Engineer. This role is a dynamic blend of Platform Engineering, Dev Ops/SRE, and Big Data Infrastructure Engineering, focused on enabling large-scale data and ML pipelines and intelligent systems. If you've architected big data platforms from the ground up and are eager to apply that expertise to consumer AI, we want to hear from you.

You'll bring:

• Deep technical expertise
• A passion for automation and observability
• Fluency in distributed systems
• Creativity to design scalable solutions
• And just as importantly: empathy, collaboration, and a growth mindset

Microsoft's mission is to empower every person and every organization on the planet to achieve more. As employees we come together with a growth mindset, innovate to empower others, and collaborate to realize our shared goals. Each day we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond.

Starting January 26, 2026, Microsoft AI (MAI) employees who live within a 50- mile commute of a designated Microsoft office in the U.S. or 25-mile commute of a non-U.S., country-specific location are expected to work from the office at least four days per week. This expectation is subject to local law and may vary by jurisdiction.

Responsibilities

• Architect and maintain scalable, reliable, and observable Big Data Infrastructure for mission-critical AI applications.
• Champion Dev Ops and SRE best practices-automated deployments, service monitoring, and incident response.
• Build a self-service big data platform that empowers data and platform engineers and researchers.
• Develop robust CI/CD pipelines and automate infrastructure provisioning using Infrastructure as Code tools (Bicep, Terraform, ARM).
• Collaborate with Data Engineers, Data Scientists, AI Researchers, and Developers to deliver secure, seamless big data workflows.
• Lead technical design reviews and uphold a clean, secure, and well-documented codebase.
• Proactively identify and resolve bottlenecks in data pipelines and infrastructure.
• Optimize system performance across storage, compute, and analytics layers.
• Partner with Security teams to enhance system security (IAM, OAuth, Kerberos).
• Embody and promote Microsoft's values:
  Respect, Integrity, Accountability, and Inclusion.

Qualifications

Required 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.

Preferred Qualifications:

• 4+ years in Big Data Infrastructure, Dev Ops, SRE, or Platform Engineering.
• 3+ years of hands-on experience managing and scaling distributed systems-from bare-metal to cloud-native environments.
• 2+ years deploying containerized applications using Kubernetes and Helm/Kustomize.
• Solid scripting and automation skills using Python, Bash, or Power Shell.
• Proven success in CI/CD pipeline management, release automation, and production troubleshooting.
• Experience working with Databricks for scalable data processing and analytics.
• Familiarity with security practices in infrastructure environments, including IAM, OAuth, and Kerberos administration.
• Proven experience with cloud-native infrastructure across Azure, AWS, or Google Cloud Platform.
• Hands-on expertise with modern data platforms like Databricks,…