Join Microsoft's Azure Data engineering team, a leader in transforming data analytics. We are building the next-generation data platform for the age of AI, powering data-first applications and fostering a data culture across Microsoft. Our mission is critical for the company's revenue, ensuring accurate and timely billing through reliable ingestion, aggregation, and processing of high-volume usage data.

This role offers the chance to design and operate large-scale distributed systems, tackle complex reliability and performance challenges, and contribute to intelligent billing and data platforms. You'll engage with cloud infrastructure, streaming technologies, data analytics, AI-driven operations, and platform capabilities, providing ample opportunities for technical growth and cross-organizational collaboration.

Key responsibilities include building cloud-scale products with a focus on efficiency, reliability, and security. You will develop and maintain end-to-end build, test, and deployment pipelines, and contribute to product architecture and design.

This role involves triaging issues, implementing solutions, and performing root cause analysis to ensure service restoration with minimal disruption. You will own components end-to-end, from requirements gathering and development to deployment and ensuring high availability. Guiding and mentoring team members, and leading broader feature development within a dev crew, are also integral aspects of this position.

A Bachelor's degree in Computer Science, Math, Software Engineering, Computer Engineering, or a related field, coupled with at least 8 years of experience in software development, architecture, data modeling, or data engineering, is required. Alternatively, a Master's degree in a related field with 8+ years of equivalent experience is acceptable.

Candidates must demonstrate the ability to collaborate effectively within multidisciplinary teams, including Software Engineers, Program Managers, and Security experts. Proven experience in designing, building, and operating large-scale, distributed cloud services with a strong emphasis on reliability, scalability, and performance is essential. A robust operational discipline, including managing live-site health and delivering consistent, high-quality outcomes, is also expected.