Principal Data Engineer

Role Description

MCAPS-Core DAAI is seeking a Principal Data Engineer to build the AI-powered platforms, intelligent agents, and data foundations that fuel Microsoft's transformation. This role combines deep software engineering, data engineering, and AI expertise to deliver scalable solutions powered by generative AI, LLMs, agentic workflows, and enterprise data platforms. The ideal candidate is a hands-on technical leader who thrives on solving complex engineering challenges and building intelligent systems that translate data into actionable business impact.

• Lead end-to-end development of cloud-native applications, APIs, and platform services, applying full-stack engineering principles across frontend, backend, integration, security, observability, testing, and continuous delivery disciplines.
• Architect and deliver next-generation AI platforms, copilots, agentic systems, and intelligent applications powered by Generative AI, Large Language Models (LLMs), and advanced reasoning capabilities.
• Design and build AI-ready data platforms and knowledge systems, scalable AI services, APIs, and orchestration frameworks that power autonomous agents, intelligent automation, and enterprise-scale workflows.
• Drive the technical strategy and architecture for Applied AI solutions, partnering across engineering, data science, product, and business teams to accelerate AI innovation and adoption.
• Create reusable AI frameworks, SDKs, and platform services that improve developer productivity, model performance, scalability, governance, and reliability.
• Establish best practices for Responsible AI, AI governance, model evaluation, security, compliance, observability, and operational excellence.
• Provide hands-on technical leadership through architecture reviews, code reviews, mentoring, and direct contribution to software, data, and AI solutions.
• Partner with business and technology leaders to identify and deliver transformational AI opportunities that enhance productivity, decision-making, and customer experiences.
• Champion customer-zero innovation by turning emerging AI technologies into scalable platforms, reusable services, and enterprise-wide solutions.

Qualifications

• 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, data modeling, or data engineering OR 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 OR equivalent experience.
• 5+ years of demonstrated experience working in data-intensive Azure environments and translating business requirements into scalable data and AI solutions. Deep expertise with Microsoft technologies, including Microsoft Fabric, Azure AI Foundry, Azure Data Platform, Synapse Analytics, Azure App Service.
• Hands-on experience developing solutions using Python and/or other modern programming languages such as C#, Java, Scala, or equivalent.
• Proven experience designing and implementing Generative AI, Large Language Model (LLM), Retrieval-Augmented Generation (RAG), semantic search, vector database, and agentic AI solutions.

Requirements

• 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 OR Bachelor's Degree in Computer Science, Math, Software Engineering, Computer Engineering, or related field AND 12+ years experience in business analytics, data science, software development, data modeling, or data engineering OR equivalent experience.
• Experience building and deploying Copilots, intelligent agents, multi-agent systems, and enterprise AI applications.
• Expertise in AI platform engineering, LLM orchestration, knowledge graphs, prompt engineering, model tuning, and AI evaluation frameworks.
• Expertise in developing and operating cloud-scale services using modern software engineering and SRE practices, with a focus on reliability, observability, automation, and service excellence.
• Experience with MLOps, LLMOps, AI observability, model governance, and production AI operations.
• Proven success leading enterprise-scale cloud, data, analytics, and AI transformation initiatives.
• Demonstrated ability to mentor engineers, foster innovation, and elevate engineering excellence across large, complex organizations.
• Strong technical leadership skills with a track record of driving architecture decisions, engineering strategy, and cross-functional execution.
• Ability to meet Microsoft, customer and / or government security screening requirements are required for this role.

Benefits

• The typical base pay range for this role across the U.S. is USD $142,800 - $274,800 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 $188,000 - $304,200 per year.
• Certain roles may be eligible for benefits and other compensation.