below marketmost similar roles pay hereabove market
This role pays more than
68%
of similar roles. Most pay
$149,500–$214,650
— the blue band above.
At the midpoint, this role pays about
$209k
versus about
$182k
for comparable roles.
Based on 240 similar postings.
Employer
About Microsoft
Microsoft Corporation is a global technology leader producing software, hardware, and cloud services including Windows, Office 365, Azure cloud platform, Xbox gaming, and Surface devices. Industry: Software & Cloud Computing
Microsoft currently has
692 open roles
on FindRole.
Listed pay typically runs
$119,800–$234,700
across 649 roles with salary data.
The Principal Data Engineer joins the MCAPS-Core Data & Applied AI team to build AI-powered platforms, intelligent agents, and data foundations. This role involves leading end-to-end development of cloud-native applications, APIs, and platform services while architecting next-generation systems powered by Generative AI and Large Language Models. You will design AI-ready data platforms, knowledge systems, and orchestration frameworks to power autonomous agents and enterprise-scale workflows. Key responsibilities include driving technical strategy for Applied AI solutions, creating reusable SDKs, and establishing best practices for Responsible AI and MLOps. Required skills include proficiency in Python, C#, Java, or Scala, alongside experience with Microsoft Fabric, Azure AI Foundry, Synapse Analytics, and Azure App Service. You will solve complex engineering challenges to translate data into actionable business impact.
What does a Data Engineer earn?
Median $167000 from 199 postings across 60 companies.
Lead end-to-end development of cloud-native applications, APIs, and platform services using full-stack engineering principles.
Architect and deliver next-generation AI platforms, copilots, and agentic systems powered by Generative AI and LLMs.
Design and build AI-ready data platforms, knowledge systems, and orchestration frameworks for enterprise-scale workflows.
Drive the technical strategy and architecture for Applied AI solutions across engineering, data science, and product teams.
Create reusable AI frameworks, SDKs, and platform services to improve developer productivity and model performance.
Establish best practices for Responsible AI, governance, security, compliance, and operational excellence.
Provide hands-on technical leadership through architecture reviews, code reviews, and direct contribution to software and AI solutions.
Turn emerging AI technologies into scalable platforms and reusable services for customer-zero innovation.
What we're looking for
Master's Degree in a related field and 4+ years of experience in business analytics, data science, software development, data modeling, or data engineering.
Bachelor's Degree in a related field and 6+ years of experience in business analytics, data science, software development, data modeling, or data engineering.
Equivalent experience to the degree and years of experience requirements.
Ability to meet Microsoft, customer, and/or government security screening requirements, including a Microsoft Cloud Background Check.
3+ years of experience working with data governance, compliance, and/or data security (preferred).
5+ years of experience in data-intensive Azure environments using technologies like Microsoft Fabric, Azure AI Foundry, and Synapse Analytics (preferred).
Proficiency in developing solutions with Python and/or modern programming languages such as C#, Java, or Scala (preferred).
Demonstrated ability to design and implement Generative AI solutions including LLMs, RAG, vector databases, and multi-agent systems (preferred).
Snowflake
AWS
Python
Data Vault
dbt
DataStage
Qlik Replicate
S3
Lambda
Data Modeling
DevOps
Agile
APIs
Data Governance
Data Quality
Metadata
Lineage
Generative AI
Microsoft Fabric
Data Engineering
SQL
Distributed Processing
big-data
Streaming
Data Modeling
Data Governance
Data Security
Schema Evolution
Data Products
AI
Software Development Lifecycle
data, lineage
Python
C#
Java
C++
JavaScript
Generative AI
Large Language Models
Agentic AI
Azure AI Foundry
Copilot Studio
Power Platform
Retrieval-Augmented Generation
Prompt Engineering
Distributed Systems
APIs
Observability
Data Governance