This role pays more than
82%
of similar roles. Most pay
$155,300–$216,300
— the shaded band above.
At the midpoint, this role pays about
$231k
versus about
$186k
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
557 open roles
on FindRole.
Listed pay typically runs
$119,800–$234,700
across 537 roles with salary data.
As a Principal Data Engineer, you will lead the architecture, development, and operation of scalable, reliable data platforms while managing complex, ambiguous problems from design through production. You will be responsible for designing ETL workflows, data pipelines, and data models, while ensuring high engineering standards regarding security, scalability, and cost. Your daily work involves building solutions using Apache Spark, Python, SQL, Delta Lake, and Parquet files, alongside provisioning resources via Infrastructure as Code and managing CI/CD pipelines with robust observability. You will also champion an AI-native approach by integrating AI-assisted development into coding and troubleshooting workflows. The role focuses on solving technical challenges in data platforms for experimentation, metrics, and scorecards, requiring expertise in distributed systems to ensure high-quality, production-grade deployments while mentoring others and collaborating across team boundaries to resolve complex system-design issues.
What does a Data Engineer earn?
Median $162000 from 190 postings across 57 companies.
Design and evolve ETL workflows, data pipelines, and data models using Spark, Python, and SQL.
Build end-to-end data solutions using distributed systems, open table formats like Delta Lake, and Parquet files.
Develop scalable APIs with robust access controls and provision resources through Infrastructure as Code.
Manage production outcomes by establishing monitoring, performing root-cause analysis, and automating deployments.
Implement AI-assisted development practices while ensuring the quality and safety of AI-generated outputs.
Make high-level system design decisions regarding scalability, resiliency, disaster recovery, and cost optimization.
Lead code reviews and integrate security, privacy, and compliance into the entire software lifecycle.
Mentor engineers and communicate technical trade-offs to align partner teams on dependencies and ownership.
What we're looking for
Bachelor's Degree in Computer Science or related field and 8+ years of technical engineering experience with coding in languages like C, C++, C#, Java, JavaScript, or Python.
Master's Degree in Computer Science or related field and 12+ years of technical engineering experience (preferred).
Bachelor's Degree in Computer Science or related field and 15+ years of technical engineering experience (preferred).
Expertise in ETL, data pipelines, data modeling, and distributed systems.
Proficiency in Apache Spark, Python, and SQL.
Experience building data platforms for experimentation, metrics, and scorecards including understanding success metrics, guardrail metrics, and data quality (preferred).
Experience in Databricks like platforms (preferred).