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Microsoft Corporation Logo Microsoft Corporation · IT - Software Development

Member of Technical Staff, Infrastructure Data & Analytics

United States, Multiple Locations 139900.00 - 274800.00 USD / Year · Job Posted February 13, 2026
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Job Description

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.

Job Responsibility

  • 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

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
  • 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
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