Senior Data Engineer

• Application and Platform Ownership: From the app code to backend web servers and middle-tier services.
• Partner Enablement: All AI-enabled experiences from partner teams are built on our platform, making us critical to their success.
• Data and Insights: We manage the data pipeline that supports business insights and operational excellence.
• End-to-End Delivery: From platform APIs and infrastructure to deployment and monitoring, ensuring reliability and scalability.

Our mission is to empower every Copilot experience by providing a robust, secure, and scalable platform that accelerates innovation across Microsoft 365.

As a Senior Data Engineer in the M365 Copilot App Platform team, you will design, build, and optimize scalable data pipelines and platforms that power advanced analytics and AI solutions. You will work closely with software engineers, data scientists, and product teams to ensure reliable, secure, and high-performance data systems that enable innovation across Microsoft’s Copilot ecosystem.

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.

• 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
• OR 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
• OR equivalent experience.
• 3+ years experience in building distributed data processing systems leveraging technologies including, but not limited to, Spark, Azure Data Lake, or Synapse

• Microsoft Cloud Background Check: This position will be required to pass the Microsoft Cloud background check upon hire/transfer and every two years thereafter.

• 5+ years of experience in data engineering or software development with a focus on large-scale data systems
• 2+ years experience developing and maintaining low/no-code dashboards and data-driven apps (e.g., Power BI, Vibe-coded apps) to enable self-service analytics for stakeholders
• Proficiency in managing machine learning data pipelines and feature engineering processes
• Proficiency in data security, privacy compliance, and governance frameworks.
• Demonstrate effective communication and collaboration skills in a dynamic, fast-paced environment
• Creativity, insightfulness, and sensitivity for a dynamic approach to problem-solving, combined with being motivated and self-driven, are essential

Data Engineering IC4 - The typical base pay range for this role across the U.S. is USD $119,800 - $234,700 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 $158,400 - $258,000 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

Single reqs: Microsoft will accept applications for the role until October 28th, 2025 

#m365 #copilot #m365copilot #ai

• Data Architecture & Pipeline Development
• Design and implement robust ETL/ELT workflows for structured and unstructured data using modern data engineering frameworks.
• Scalable Data Solutions:
  Build distributed data processing systems leveraging technologies such as Spark, Azure Data Lake, and Synapse.
• Data Quality & Governance:
  Establish standards for data integrity, lineage, and compliance with enterprise security and privacy policies.
• Performance Optimization:
  Monitor and tune data pipelines for efficiency, scalability, and cost optimization.
• Data Visualization & Low-Code Solutions:
  Develop and maintain low/no-code dashboards and data-driven apps (e.g., Power BI, Vibe-coded apps) to enable self-service analytics for stakeholders.
• Experimentation Infrastructure Support:
  Help maintain and enhance experiment platforms, including Cosmos streams and VC(s), ensuring reliability and scalability for A/B testing and feature experimentation.
• Collaboration & Mentorship:
  Partner with cross-functional teams to integrate data solutions into AI products and mentor team members/engineers on best practices.
• Innovation & Continuous Improvement:
  Evaluate emerging technologies and contribute to architectural decisions for next-generation data platforms.