About The Position
We are seeking experienced Infrastructure Data & Analytics Engineers to join our Microsoft AI team and own the end-to-end technical vision and execution for infrastructure analytics, turning raw telemetry into trusted, decision-quality insights on utilization, capacity, readiness, and efficiency. This role is critical to helping the Microsoft AI, SuperIntelligence leadership make informed investment and planning decisions at scale. Microsoft Superintelligence Team Microsoft Superintelligence team’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. This role is part of Microsoft AI's Superintelligence Team. The MAIST is a startup-like team inside Microsoft AI, created to push the boundaries of AI toward Humanist Superintelligence—ultra-capable systems that remain controllable, safety-aligned, and anchored to human values. Our mission is to create AI that amplifies human potential while ensuring humanity remains firmly in control. We aim to deliver breakthroughs that benefit society—advancing science, education, and global well-being. We’re also fortunate to partner with incredible product teams giving our models the chance to reach billions of users and create immense positive impact. If you’re a brilliant, highly-ambitious and low ego individual, you’ll fit right in—come and join us as we work on our next generation of models! 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. By applying to this Mountain View, CA position, you are required to be local to the San Francisco area and in office 4 days a week.
Requirements
- Bachelor’s degree in computer science, or related technical field AND 8+ years technical engineering experience with data engineering, analytics, or data science, with increasing technical ownership in startup environment AND 6+ years experience with distributed data processing frameworks and large-scale data systems OR equivalent experience.
Nice To Haves
- Master's Degree in Computer Science or related technical field AND 12+ years technical engineering experience with technical engineering experience with data engineering, analytics, or data science, with increasing technical ownership in startup environment AND 10+ years experience with distributed data processing frameworks and large-scale data systems OR equivalent experience.
- Proven technical leadership in data engineering, analytics platforms, or large-scale telemetry systems.
- Hands-on experience with ETL orchestration frameworks such as Airflow, Dagster, or similar.
- Strong communication skills; can explain complex systems clearly to senior leader.
Responsibilities
- Act as the technical lead and owner for infrastructure analytics across compute, storage, and networking.
- Design and build durable, scalable data pipelines that ingest telemetry from clusters, schedulers, health systems, and capacity trackers into Data Warehouse
- Define and standardize core metrics and semantics (e.g., utilization, occupancy, MFU, goodput, capacity readiness, delivery-to-production).
- Architect and maintain self-service dashboards and APIs for fleet, cluster, and squad-level visibility.
- Partner closely with stakeholders across Supercomputing Infra, Researchers, Strategy and Executives to ensure metrics reflect operational and business reality.
- Implement robust and fault-tolerant systems for data ingestion and processing.
- Lead data architecture and engineering decisions, applying strong technical judgment to proactively shape executive-level discussions and decisions.
- Identify data gaps and instrumentation issues; drive fixes by influencing upstream engineering teams.
- Establish data quality, validation, documentation, and governance so metrics are trusted and repeatable.
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What This Job Offers
Job Type
Full-time
Career Level
Mid Level
