Principal Data Engineer

Microsoft

Confirmed live yesterday High trust

Quick summary

Work type: On-site
Location: —
Salary: $142,800–$274,800 / yr
Posted: 31 days ago
Freshness: Confirmed live yesterday
Closes: Feb 7, 2027

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $191k

This role $209k

$120k most similar roles pay here $291k

This role pays more than 68% of similar roles. Most pay $169,887–$211,200 — the shaded band above. At the midpoint, this role pays about $209k versus about $191k 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 598 open roles on FindRole.

Listed pay typically runs $119,800–$234,700 across 586 roles with salary data.

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At a glance

TL;DR · Principal Data Engineer

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As a Principal Data Engineer - CoreAI, you will serve as a technical leader within the CoreAI team, shaping the data and analytics foundations for AI platforms. You will define architectural direction, set engineering standards, and manage multi-team roadmaps to ensure scalable, reliable, and cost-effective analytics for AI workloads. Your daily responsibilities include designing and optimizing large-scale data pipelines, developing ETL/ELT workflows for high-volume data, and implementing rigorous data governance, lineage, and security protocols. You will collaborate with data scientists and product managers to build semantic layers and self-service tools. The role requires expertise in Spark, SQL, PySpark, Azure Data Lake, Synapse, and Azure Data Explorer. You will solve complex problems regarding data quality and infrastructure for AI-driven products while mentoring senior engineers and leading technical projects in cloud environments.

What does a Data Engineer earn?

Median $183138 from 214 postings across 58 companies.

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Skills

Azure Spark SQL PySpark Azure Data Lake Synapse Azure Data Explorer ETL ELT Data Modeling Data Governance Data Pipelines Algorithms Data Structures

What you'll do

Define end-to-end data and analytics architecture for CoreAI and Foundry platforms to support scalable AI workloads.
Design, build, and optimize large-scale, robust data pipelines for high-volume and high-velocity data sources.
Develop and extend scalable ETL/ELT workflows to ensure reliable ingestion, transformation, and storage of data.
Implement rigorous data quality, lineage, security, and compliance protocols to ensure trustworthy datasets.
Build data models, semantic layers, and tools to enable self-service analytics for various teams.
Translate business requirements from stakeholders into technical solutions and actionable product roadmaps.
Mentor senior engineers and technical leads while guiding complex design decisions and engineering standards.

What we're looking for

Master's degree in Computer Science, Math, Software Engineering, or related field and 4+ years of experience in data engineering or related fields.
Bachelor's degree in Computer Science, Math, Software Engineering, or related field and 6+ years of experience in data engineering or related fields.
Equivalent experience to the specified degrees and years of experience is acceptable.
Ability to pass a Microsoft Cloud background check.
Experience architecting and operating large-scale distributed data systems in cloud environments, preferably Azure (preferred).
Ability to write clean code using core algorithms, data structures, and analytics-oriented problem solving (preferred).
Extensive experience implementing and optimizing data pipelines and distributed systems like Spark, Synapse, or SQL databases (preferred).
Expertise with modern data engineering languages and frameworks such as PySpark and SQL (preferred).

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