Description
Job Description
Overview
As Microsoft continues to push the boundaries of AI, we are on the lookout for passionate individuals to work with us on the most interesting and challenging AI questions of our time. Our vision is bold and broad — to build systems that have true artificial intelligence across agents, applications, services, and infrastructure. It’s also inclusive: we aim to make AI accessible to all — consumers, businesses, developers — so that everyone can realize its benefits.
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. While expertise in real-time systems, large language models (LLMs), and machine learning models is strongly preferred, we welcome candidates with broad data engineering experience and a passion for solving dynamic AI challenges.
Microsoft’s mission is to empower every person and every organization on the planet to achieve more. As employees we come together with a growth mindset, innovate to empower others, and collaborate to realize our shared goals. Each day we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond.
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.
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.
- Workflow Optimization: Optimize workflows to ensure seamless integration and accessibility of data.
- Infrastructure Performance: Implement performance monitoring, troubleshoot issues, and develop scalable solutions to ensure reliability.
Qualifications
Required Qualifications:
- Bachelor's Degree in Computer Science, Math, Software Engineering, Computer Engineering, or related field AND 4 years experience in business analytics, data science, software development, data modeling or data engineering work
- OR Master's Degree in Computer Science, Math, Software Engineering, Computer Engineering, or related field AND 3 years experience in business analytics, data science, software development, data modeling or data engineering work
- OR equivalent experience.
- 3 years of experience shipping product at scale
Preferred Qualifications:
- Bachelor's Degree in Computer Science, Math, Software Engineering, Computer Engineering, or related field AND 10 years experience in business analytics, data science, software development, data modeling, or data engineering work
- OR Master's Degree in Computer Science, Math, Software Engineering, Computer Engineering, or related field AND 8 years experience in business analytics, data science, software development, data modeling or data engineering work
- OR equivalent experience.
Data Engineering IC4 - The typical base pay range for this role across the U.S. is USD $117,200 - $229,200 per year. There is a different range applicable to specific work locations, within the San Francisco Bay area and New York City metropolitan area, and the base pay range for this role in those locations is USD $153,600 - $250,200 per year.
Data Engineering IC5 - The typical base pay range for this role across the U.S. is USD $137,600 - $267,000 per year. There is a different range applicable to specific work locations, within the San Francisco Bay area and New York City metropolitan area, and the base pay range for this role in those locations is USD $180,400 - $294,000 per year.
Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here: https://careers.microsoft.com/us/en/us-corporate-pay
Microsoft will accept applications and processes offers for these roles on an ongoing basis.
#MicrosoftAI #Copilot
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