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Senior Data Engineer - AI Infrastructure
Microsoft
H1B ✓Hybridsenior levelPosted April 17, 2026
About the Role
Design and implement large-scale data pipelines using PySpark while maintaining high standards for data correctness and reliability. Collaborate with data scientists and platform engineers to optimize data models and ensure efficient ingestion and storage.
Requirements
Requires a Bachelor's or Master's degree in a technical field and at least 3-4 years of relevant experience in data engineering or software development. Candidates must demonstrate proficiency in distributed processing frameworks and the ability to pass specialized Microsoft security screenings.
Full Job Description
Overview
Responsibilities
Qualifications
We are building a large-scale data platform that transforms raw system logs into high-quality, structured datasets used for experimentation and analytics. The platform processes terabytes to petabytes of data daily and serves as a foundational asset for multiple teams.
This Senior Data Engineer - AI Infrastrucute role focuses on designing and implementing data pipelines, ensuring correctness, and building scalable data models. You will work closely with data scientists and platform engineers to ensure that data is accurate, reliable, and usable for downstream decision-making.
We are looking for engineers who care deeply about data correctness, understand how systems behave at scale, and can translate complex data into well-structured, reliable datasets.
Responsibilities
- Design and implement large-scale data pipelines using PySpark and distributed processing frameworks
Build and maintain data models that accurately represent underlying system behavior and business logic
Ensure high standards of data correctness, completeness, and consistency across datasets
Develop validation, monitoring, and alerting mechanisms to detect data quality issues
Partner with data scientists to support experimentation and analytics use cases
Collaborate with platform engineers to ensure efficient data ingestion, processing, and storage
Optimize pipelines for performance, scalability, and cost efficiency
Define and enforce best practices for schema design, data transformations, and pipeline reliability
Qualifications
Required/Minimum Qualifications:
Master's Degree in Computer Science, Math, Software Engineering, Computer Engineering, or related field AND 3+ 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 4+ years experience in business analytics, data science, software development, data modeling, or data engineering OR equivalent experience.
Other Requirements:
Ability to meet Microsoft, customer and/or government security screening requirements are required for this role. These requirements include, but are not limited to the following specialized security screenings: Microsoft Cloud Background Check: This position will be required to pass the Microsoft Cloud Background Check upon hire/transfer and every two years thereafter.
Preferred Qualifications:
Experience with Azure technologies such as:
ADLS Gen2 (Blob Storage)
Synapse Spark
Azure Data Explorer (ADX)
Experience working with structured and semi-structured data (e.g., JSON logs)
Familiarity with experimentation and analytics workflows
Experience with orchestration tools (e.g., Airflow)
Exposure to privacy, compliance, and secure data handling practices
5+ years of experience in data engineering or software engineering with a strong focus on data systems
- Strong experience with PySpark or similar distributed data processing frameworks
- Experience building and operating large-scale data pipelines
- Strong understanding of data modeling and schema design
- Experience ensuring data quality and correctness in production systems
- Proficiency in Python
- Experience working with cloud-based data platforms (Azure, AWS, or GCP)
- Ability to reason about data at scale, including performance and failure modes
#aiinfra
Data Engineering IC4 - The typical base pay range for this role across the U.S. is USD $119,800 - $234,700 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 $158,400 - $258,000 per year.
Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here:
https://careers.microsoft.com/us/en/us-corporate-pay
This position will be open for a minimum of 5 days, with applications accepted on an ongoing basis until the position is filled.
Microsoft is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship, color, family or medical care leave, gender identity or expression, genetic information, immigration status, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran or military status, race, ethnicity, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable local laws, regulations and ordinances. If you need assistance with religious accommodations and/or a reasonable accommodation due to a disability during the application process, read more about requesting accommodations.