Microsoft's Azure Data Analytics group is building next-generation data platforms like Microsoft Fabric, Synapse Analytics, and Power BI. The team needs to deliver scalable, lakehouse-native, serverless data warehousing and advanced analytics solutions to empower customers with real-time insights and intelligent decision-making. Interns will contribute to high-performance SQL and Spark runtimes and massive-scale infrastructure.
Requirements
- Coursework/projects or prior experience with low-level SIMD assembly, GPU programming, low-level systems programming, and/or C++.
Responsibilities
- Applies engineering principles to solve complex problems through sound and creative engineering, with a focus on query execution performance across CPU and GPU architectures.
- Works with appropriate stakeholders to determine user requirements for features that impact low-level systems performance, including memory bandwidth optimization, SIMD execution, and runtime efficiency.
- Quickly learns and applies advanced engineering methods such as SIMD assembly (e.g., AVX-512), GPU programming, and C++, integrating them into high-performance query execution workflows.
- Seeks feedback and applies internal or industry best practices to improve technical solutions.
- Demonstrates skill in time management and completing software projects in a cooperative team environment, contributing to scalable and efficient data analytics infrastructure.
- Reviews current developments and proactively seeks new knowledge that will improve the availability, reliability, efficiency, observability, and performance of query execution systems—while driving consistency in monitoring and operations at scale.
Other
- Enrolled in a full time bachelor's or master’s program in Computer Science, Engineering, or related field during the academic term immediately before the internship.
- Must have at least 1 semester/term remaining following the completion of the internship.
- One year of programming experience in an object-oriented language.
- Ability to demonstrate an understanding of computer science fundamentals, including data structures and algorithms.
- 3 days / week in-office
