Data Engineering Manager, Microsoft AI - Copilot

Overview

As Microsoft continues to push the boundaries of AI, we are seeking an experienced Data Engineering Manager, Microsoft AI - Copilot to help build mission-critical data pipelines that ingest, process, and publish data streams from our personal AI, Copilot systems. We're looking for someone who possesses technical prowess, a methodical approach to problem-solving, proficiency in big data processing technologies, and a mastery of templating to architect solutions that stand the test of time. This role also requires an abundance of positive energy, empathy, and kindness, in addition to being highly effective. The Data Platform Engineering team is responsible for building core data pipelines that help fine-tune models, support introspection, and retrospection of data so that we can constantly evolve and improve human AI interactions.

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.

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

• Build scalable data pipelines for sourcing, transforming, and publishing data assets for AI use cases.
• Work collaboratively with other Platform, infrastructure, application engineers, as well as AI Researchers, to build next-generation data platform products and services.
• Ship high-quality, well-tested, secure, and maintainable code.
• Find a path to get things done despite roadblocks to get your work into the hands of users quickly and iteratively.
• Enjoy working in a fast-paced, design-driven, product development cycle.
• Embody our Culture and Values.
• Ability to manage a small team of 4 or 5 senior data engineers, talent management experiences.
• Additionally, the candidate will have experiences owning engineering and operational excellence for data platform which includes PR reviews, code quality, engineering productivity, etc.

Required Qualifications

• Bachelor's Degree in Computer Science, Math, Software Engineering, Computer Engineering, or related field AND 6+ 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 4+ years experience in business analytics, data science, software development, or data engineering work OR equivalent experience.

Preferred Qualifications

• 4+ years technical engineering experience building data processing applications (batch and streaming) with coding in languages including, but not limited to, Python, Java, Spark, SQL.
• Experience working with Apache Hadoop ecosystem, Kafka, NoSQL, etc.
• 3+ years experience with data governance, data compliance and/or data security.
• 2+ years' experience building scalable services on top of public cloud infrastructure like Azure, AWS, or GCP.
• Extensive use of datastores like RDBMS, key-value stores, etc.
• 2+ years' experience building distributed systems at scale and extensive systems knowledge that spans bare-metal hosts to containers to networking.
• Ability to identify, analyze, and resolve complex technical issues, ensuring optimal performance, scalability, and user experience.
• Dedication to writing clean, maintainable, and well-documented code with a focus on application quality, performance, and security.
• Demonstrated interpersonal skills and ability to work closely with cross-functional teams, including product managers, designers, and other engineers.
• Ability to clearly communicate complex technical concepts to both technical and non-technical stakeholders.
• Interest in learning new technologies and staying up to date with industry trends, best practices, and emerging technologies in web development and AI.
• Ability to work in a fast-paced environment, manage multiple priorities, and adapt to changing requirements and deadlines.

Key skills/competency

• Data Engineering
• Data Pipelines
• Big Data Technologies
• Cloud Computing (Azure, AWS, GCP)
• Python/Java/Spark/SQL
• Apache Hadoop
• Kafka
• NoSQL
• Distributed Systems
• Data Governance