Principal Software Engineer

Microsoft•,
•$142,800 - $304,200

About The Position

The Principal Software Engineer provides technical leadership for the architecture and evolution of large-scale distributed data platforms that ingest, process, enrich, store, and publish network telemetry and operational data for Microsoft Azure. The role defines engineering strategy and architectural direction for systems where scale, availability, data quality, performance, and operational reliability are critical. It addresses ambiguous, cross-cutting technical challenges, establishes engineering patterns and platform abstractions, and influences investments across organizational boundaries while partnering with teams throughout Azure Networking. The engineer shapes cloud-scale data platform architecture and technical strategy across complex distributed systems, influencing how network data supports automated and intelligent operations in Azure. The position also mentors engineers and technical leaders, raises engineering standards, and helps the organization make durable architectural decisions that support sustained growth and innovation.

Requirements

  • Bachelor's degree in Computer Science or a related technical field and at least 6 years of technical engineering experience coding in languages including C, C++, C#, Java, Python, Go, or Rust, or equivalent experience.
  • Ability to meet Microsoft, customer, and/or government security screening requirements, including passing the Microsoft Cloud Background Check upon hire or transfer and every two years thereafter.

Nice To Haves

  • Master's degree in Computer Science or a related technical field and at least 8 years of technical engineering experience coding in languages including C, C++, C#, Java, JavaScript, or Python; or a bachelor's degree in a related field and at least 12 years of such experience; or equivalent experience.
  • At least 1 year of extensive experience architecting, building, and operating large-scale distributed systems and high-volume data platforms in production environments.
  • At least 1 year of deep technical expertise in distributed systems, data processing, streaming and batch architectures, with demonstrated ability to design for scalability, availability, resiliency, performance, and data quality.
  • At least 1 year of experience designing cloud-scale platforms for telemetry, monitoring, diagnostics, automation, or other data-driven operational capabilities.
  • At least 1 year of experience applying artificial intelligence, machine learning, or agentic software development approaches to production systems, developer productivity, automation, diagnostics, or operational scenarios.

Responsibilities

  • Provide technical leadership and define the architectural direction for highly scalable, reliable distributed data platforms that ingest, process, enrich, store, and publish network telemetry and operational data.
  • Lead the design and evolution of cloud-scale streaming and batch data systems, solving complex and ambiguous engineering problems involving scalability, availability, performance, resiliency, data quality, and operational efficiency.
  • Drive long-term technical strategy across multiple teams, identify opportunities for product-level impact, and establish reusable architectures, engineering patterns, and platform capabilities.
  • Partner across Microsoft Azure Networking and the broader Microsoft Azure organization to lead architectural and design reviews, align technical investments, manage cross-system dependencies, and deliver cohesive solutions.
  • Own critical capabilities end to end, from architecture and design through implementation, production readiness, operation, and continuous improvement, ensuring security, reliability, maintainability, and engineering quality.
  • Identify systemic technical risks and drive improvements in design, code quality, testing, observability, performance, reliability, and operational practices.
  • Mentor and influence engineers and technical leaders, develop engineering capability across teams, and foster sound technical decision-making, collaboration, accountability, and continuous learning.
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