Software Engineer II - People Skills Data Platform
Microsoft
Software Engineer II - People Skills Data Platform
Redmond, Washington, United States
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Overview
Our charter includes:
- Designing and maintaining data connectors and pipelines that ingest, transform, and synchronize skills and people intelligence data across Microsoft systems and external sources.
- Ensuring data scalability, schema definition, and governance across the People Intelligence space to enable interoperability and consistency.
- Driving reliability, performance, and observability through robust engineering and operational practices.
- Building telemetry, alerting, and health monitoring frameworks to continuously improve service quality.
- Implementing compliance, privacy, and licensing enforcement across all data movement and processing layers.
- Partnering with Viva Learning, Graph, and Copilot teams to ensure secure and high-quality data availability.
We are looking for a Software Engineer II - People Skills Data Platform. For this Role you will design, develop, and operate data connectors, pipelines, and schema models for the People Skills Data Platform. This role is central to enabling skills' intelligence across Microsoft Viva and M365 Copilot, empowering organizations to manage and grow workforce skills through AI-driven insights and scalable data solutions.
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.
Qualifications
Required Qualifications:
- Bachelor's Degree in Computer Science or related technical field AND 2+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python
- OR equivalent experience.
- 2+ years experience designing, developing, and operating high-performance data services, distributed systems, and intelligent APIs.
- Proven ability to implement and maintain scalable data pipelines and connectors.
- Solid understanding of data schema definition, evolution, and governance.
- Familiarity with compliance, privacy, and licensing enforcement in data platforms.
- Demonstrated collaboration skills with cross-functional teams in large-scale enterprise environments.
- Participation in design/code reviews and operational excellence initiatives.
Other Requirements:
- Microsoft Cloud Background Check: This position will be required to pass the Microsoft Cloud background check upon hire/transfer and every two years thereafter.
- Expertise in data engineering, AI, and enterprise-scale platforms.
- Skills in building telemetry, alerting, and health monitoring frameworks.
- Expertise in data scalability, schema standardization, and governance.
- Ability to drive continuous innovation while ensuring compliance and security.
- Solid analytical and problem-solving skills, with a focus on operational excellence.
Software Engineering IC3 - The typical base pay range for this role across the U.S. is USD $100,600 - $199,000 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 $131,400 - $215,400 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 for the role until Novemeber 5, 2025.
#DPG #PeopleSkills #M365 #Copilot
Responsibilities
- Develop and maintain data pipelines for effective ingestion, transformation, and synchronization of skills and people intelligence data.
- Design and enhance data connectors to support seamless integration between Microsoft platforms and external sources.
- Define and update data schemas to ensure consistency and interoperability within the People Intelligence ecosystem.
- Improve system reliability and operational visibility by advancing telemetry and monitoring capabilities.
- Collaborate with partner teams to safeguard data integrity, compliance, and privacy across all workflows.
- Engage in code reviews, participate in on-call rotations, and drive continuous improvement using AI-driven approaches for engineering and operational excellence.