Member of Technical Staff - 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. Its also inclusive: we aim to make AI accessible to all consumers, businesses, developers so that everyone can realize its benefits.

Were looking for a seasoned Data Infrastructure Engineer. This role is a dynamic blend of Platform Engineering, DevOps/SRE, and Big Data Infrastructure Engineering, focused on enabling large-scale data and ML pipelines and intelligent systems. If youve architected big data platforms from the ground up and are eager to apply that expertise to consumer AI, we want to hear from you.

Youll 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
  
  

Microsofts 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.

Qualifications

Required Qualifications:

• Bachelor's Degree in Computer Science, Mathematics, Software Engineering, Computer Engineering, or related field AND 6 years experience in big data engineering, data modeling and data pipeline engineering workOR Master's Degree in Computer Science, Math, Software Engineering, Computer Engineering, or related field AND 4 year(s) experience in software development, or data engineering workOR equivalent experience.
• 5 years experience in Big Data Infrastructure, DevOps, SRE, or Platform Engineering, and hands-on experience managing and scaling distributed systemsfrom bare-metal to cloud-native environments.
• 5 years experience deploying containerized applications using Kubernetes and Helm/Kustomize.
• 5 years experience in scripting and automation skills using Python, Bash, or PowerShell.
• 5 years experience working with Databricks for scalable data processing and analytics.
  
  

Preferred Qualifications

• Proven experience with cloud-native infrastructure across Azure, AWS, or GCP.
• Hands-on expertise with modern data platforms like Databricks
• Deep understanding of data storage and processing technologies:Relational & NoSQL databasesKey-value storesSpark compute enginesDistributed file systems (e.g., HDFS, ADLS Gen2)Messaging systems (e.g., Event Hub, Kafka, RabbitMQ)
• Proven success in CI/CD pipeline management, release automation, and production troubleshooting.
• Familiarity with security practices in infrastructure environments, including IAM, OAuth, and Kerberos administration.
• Capacity planning and incident management for large-scale big data systems.
• Solid collaboration history with Data Engineers, Data Scientists, ML Engineers, Networking, and Security teams.
• Familiarity with modern web stacks: TypeScript, Node.js, React, and optionally PHP.
• Exposure to agentic workflows, deep learning, or AI frameworks.
• Practical experience integrating LLMs (e.g., GPT-based models) into daily workflowsautomating documentation, code generation, reviews, and operational intelligence.
• Solid grasp of prompt engineering techniques to design, optimize, and evaluate interactions with LLMs.
• Demonstrated ability to troubleshoot and resolve complex performance and scalability issues across infrastructure layers.
• Excellent interpersonal and communication skills, with a solid passion for mentorship and continuous learning.
• Experience applying LLMs to DevOps workflows, enhancing incident response, and streamlining cross-functional collaboration.
  
  

Data Engineering IC5 - The typical base pay range for this role across the U.S. is USD $139,900 - $274,800 per year. There is a different range applicable to specific work locations, within the San Francisco Bay area and New York City metropolitan area, and the base pay range for this role in those locations is USD $188,000 - $304,200 per year.

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 31, 2025

#MicrosoftAI

Responsibilities

• Architect and maintain scalable, reliable, and observable Big Data Infrastructure for mission-critical AI applications.
• Champion DevOps and SRE best practicesautomated 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 Microsofts values: Respect, Integrity, Accountability, and Inclusion.
  
  

Benefits/perks listed below may vary depending on the nature of your employment with Microsoft and the country where you work.Industry leading healthcareEducational resourcesDiscounts on products and servicesSavings and investmentsMaternity and paternity leaveGenerous time awayGiving programsOpportunities to network and connect