Principal Data Engineer

Microsoft

Confirmed live 2 days ago High trust
Remote

Quick summary

Work type
Remote
Location
Remote
Salary
$142,800–$274,800 / yr
Posted
8 days ago
Freshness
Confirmed live 2 days ago
Closes
Mar 16, 2027

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $185k
This role $209k
$127k most similar roles pay here $291k

This role pays more than 71% of similar roles. Most pay $155,175–$214,500 — the shaded band above. At the midpoint, this role pays about $209k versus about $185k 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 644 open roles on FindRole.

Listed pay typically runs $119,800–$234,700 across 624 roles with salary data.

Most-posted roles

View all roles at Microsoft

At a glance

TL;DR · Principal Data Engineer

The Principal Data Engineer joins the MCAPS-Core Data & Applied AI team to build AI-powered platforms, intelligent agents, and data foundations that drive enterprise transformation. This role involves leading the end-to-end development of cloud-native applications, APIs, and platform services while architecting next-generation systems powered by Generative AI, Large Language Models, and agentic workflows. The engineer will design AI-ready data platforms, knowledge systems, and orchestration frameworks to power autonomous agents and enterprise-scale workflows. Key technical requirements include proficiency in Python, C#, Java, or Scala, alongside expertise in Microsoft Fabric, Azure AI Foundry, Synapse Analytics, and Azure App Service. Candidates must demonstrate experience with Retrieval-Augmented Generation, semantic search, vector databases, and MLOps. The role focuses on solving complex engineering challenges by turning emerging technologies into scalable services that improve productivity and decision-making through advanced analytics and automated systems.

What does a Data Engineer earn?

Median $162000 from 205 postings across 57 companies.

See salary data

What you'll do

  • 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.
  • Develop reusable AI frameworks, SDKs, and platform services to improve developer productivity and model performance.
  • Establish best practices for Responsible AI, including governance, security, compliance, and operational excellence.
  • Provide hands-on technical leadership through architecture reviews, code reviews, and mentoring of engineering teams.
  • Translate emerging AI technologies into scalable platforms and enterprise-wide solutions to enhance customer experience.

What we're looking for

  • Master's degree in a relevant field and 4+ years of experience in data science or engineering, or a Bachelor's degree and 6+ years of experience.
  • Master's degree and 8+ years of experience, or a Bachelor's degree and 12+ years of experience (preferred).
  • 5+ years of experience in data-intensive Azure environments using technologies like Microsoft Fabric, Azure AI Foundry, and Synapse Analytics.
  • Hands-on experience developing solutions with Python or other modern languages like C#, Java, or Scala.
  • Proven experience implementing Generative AI, LLMs, RAG, semantic search, vector databases, and agentic AI solutions.
  • Experience building Copilots, multi-agent systems, and enterprise AI applications (preferred).
  • Expertise in AI platform engineering, LLM orchestration, knowledge graphs, prompt engineering, and MLOps/LLMOps (preferred).
  • Ability to pass the Microsoft Cloud Background Check (required).

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