Microsoft AI (MAI) is seeking an experienced Data Engineer to join the Growth team and contribute to the evolution of AI systems, with a focus on the personal AI assistant, Copilot. In this role, you will manage critical data pipelines and systems that drive the intelligence behind our products.
Requirements
- Azure Tech Stack Familiarity: Demonstrate proficiency with tools and services within the Azure ecosystem, such as Azure Data Factory, Azure Databricks, Azure Synapse Analytics, Azure Stream Analytics, and Azure Machine Learning.
- Build code to extract raw data, validate its quality, and transform it for downstream compatibility
- Design, develop, and maintain scalable data pipelines for efficient large-scale dataset integration using appropriate technologies.
- Integrate real-time and batch-processing pipelines to improve workflows and enhance user experience.
- Collaborate with machine learning engineers to support data preparation, feature engineering, and model evaluation for machine learning models.
- Work with data scientists to identify opportunities, conduct analyses, and drive data-driven decisions for AI initiatives.
- Manage feature storage systems and develop real-time streaming pipelines for low-latency data processing, using tools like PySpark or similar.
Responsibilities
- Azure Tech Stack Familiarity: Demonstrate proficiency with tools and services within the Azure ecosystem, such as Azure Data Factory, Azure Databricks, Azure Synapse Analytics, Azure Stream Analytics, and Azure Machine Learning.
- Data Extraction and Transformation: Build code to extract raw data, validate its quality, and transform it for downstream compatibility
- Pipeline Development: Design, develop, and maintain scalable data pipelines for efficient large-scale dataset integration using appropriate technologies.
- Pipeline Integration: Integrate real-time and batch-processing pipelines to improve workflows and enhance user experience.
- ML Collaboration: Collaborate with machine learning engineers to support data preparation, feature engineering, and model evaluation for machine learning models.
- DS Collaboration: Work with data scientists to identify opportunities, conduct analyses, and drive data-driven decisions for AI initiatives.
- Feature Storage Management: Manage feature storage systems and develop real-time streaming pipelines for low-latency data processing, using tools like PySpark or similar.
Other
- By applying to this Mountain View, CA position, you are required to be local to San Francisco area and in office 3 days a week.
- Starting January 26, 2026, MAI employees are expected to work from a designated Microsoft office at least four days a week if they live within 50 miles (U.S.) or 25 miles (non-U.S., country-specific) of that location.
- This expectation is subject to local law and may vary by jurisdiction.
- Microsoft will accept applications and processes offers for these roles on an ongoing basis.
