Software Engineering M365 Copilot App Platform at Microsoft

Redmond, Washington, United States -

Full Time

Start Date

Immediate

Expiry Date

10 Apr, 26

Salary

234700.0

Posted On

10 Jan, 26

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Data Engineering, ETL, ELT, Data Processing, Spark, Azure Data Lake, Synapse, Data Quality, Data Governance, Performance Optimization, Data Visualization, Power BI, Collaboration, Mentorship, Innovation, Continuous Improvement

Industry

Software Development

Description

Overview The M365 Copilot App Platform team delivers the foundational platform that powers the Microsoft 365 Copilot app. We provide the core platform APIs, deployment pipelines, telemetry instrumentation, and infrastructure that enable Copilot experiences across web, Windows, and Mac. Our responsibilities span: · 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 Software 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. Responsibilities 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 member/engineers on best practices. Innovation & Continuous Improvement: Evaluate emerging technologies and contribute to architectural decisions for next-generation data platforms. Qualifications Required Qualifications: Bachelor's Degree in Computer Science or related technical field AND 4+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python OR equivalent experience. Other Requirements: Ability to meet Microsoft, customer and/or government security screening requirements are required for this role. These requirements include but are not limited to the following specialized security screenings: Microsoft Cloud Background Check: This position will be required to pass the Microsoft Cloud background check upon hire/transfer and every two years thereafter. Preferred Qualifications: Master's Degree in Computer Science or related technical field AND 6+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python OR Bachelor's Degree in Computer Science or related technical field AND 8+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python OR equivalent experience. #m365 #copilot #m365copilot #ai Software 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 This position will be open for a minimum of 5 days, with applications accepted on an ongoing basis until the position is filled. Microsoft is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship, color, family or medical care leave, gender identity or expression, genetic information, immigration status, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran or military status, race, ethnicity, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable local laws, regulations and ordinances. If you need assistance with religious accommodations and/or a reasonable accommodation due to a disability during the application process, read more about requesting accommodations.

Responsibilities

Design and implement robust ETL/ELT workflows for structured and unstructured data. Build scalable data solutions and ensure the reliability and scalability of data systems.