TL;DR

MTS – Data Engineering (AI): Architecting and implementing data backbones for Microsoft's Copilot, building lightning-fast ETL pipelines for massive scale and crafting experimentation frameworks. Focus on designing scalable data architectures, ensuring robust data quality and integrity, and optimizing pipeline performance for machine learning model training and inference.

Location: Hybrid, required to be local to the San Francisco area or Redmond area, United States, and in office 3 days a week. The role is based in Mountain View, with salary ranges also applicable to the New York City metropolitan area.

Salary: USD $220,800 – $331,200 per year (applicable to Software Engineering IC6 in San Francisco Bay Area and New York City metropolitan area; other ranges available for different IC levels and US locations).

Company

%hirify_global%'s mission is to empower every person and every organization on the planet to achieve more.

What you will do

Build, maintain, and enhance data ETL pipelines for processing large-scale data with low latency and high throughput for Copilot operations.
Design and maintain high throughput, low latency experimentation reporting pipelines for measuring model performance and user engagement.
Own data quality initiatives, including monitoring, alerting, validation, and remediation processes to ensure data integrity.
Develop and maintain data infrastructure supporting real-time and batch processing for machine learning model training and inference.
Collaborate with ML engineers and data scientists to optimize data access patterns and improve pipeline performance.

Requirements

Master’s Degree in Computer Science or related field AND 4+ years experience OR Bachelor’s Degree AND 6+ years experience in data engineering or related fields.
Experience building and maintaining production data pipelines at scale using distributed processing frameworks.
Proficiency in writing production-quality Python, Scala, or Java code for data processing applications.
Experience with technologies such as Apache Spark, Kafka, or similar distributed processing frameworks.
Required to be local to the San Francisco area or Redmond area, United States, and in office 3 days a week.

Nice to have

Experience building and scaling experimentation frameworks.
Familiarity with cloud data platforms (Azure, AWS, or GCP) and their data services.
Experience with data orchestration frameworks such as Airflow, Prefect, Dagster, and containerization technologies (Docker, Kubernetes).
Demonstrated experience with data quality frameworks and monitoring solutions.

Culture & Benefits

Work within a culture valuing growth mindset, innovation, collaboration, respect, integrity, and accountability.
Opportunity to build world-class data products that make a real impact on millions of users worldwide.
Freedom to innovate and support from brilliant teammates in a fast-paced environment.
Access to comprehensive benefits and compensation details via the Microsoft careers website.