1 month ago
Base Salary
$166k - $331k/yr
Responsibilities
- Lead architecture for ETL workflows, data pipelines, data models, and scalable data platforms.
- Build and operate end-to-end data solutions using Spark or similar distributed systems, Delta Lake, Parquet, Python, and SQL.
- Develop scalable APIs, data access controls, and RBAC; provision resources through Infrastructure as Code and deliver production deployments with CI/CD.
- Own complex system-design decisions addressing dependencies, scalability, resiliency, disaster recovery, and cost.
- Apply AI-assisted practices across design, coding, testing, and troubleshooting while validating AI-generated work.
- Establish monitoring and operational readiness, resolve incidents, perform root-cause analysis, and implement preventive improvements.
- Lead design and code reviews, strengthen testing, and incorporate security, privacy, and compliance throughout the solution lifecycle.
- Collaborate across teams, communicate technical trade-offs, mentor engineers, and improve team capabilities.
Requirements
- Bachelor’s degree in Computer Science or a related technical field and 8+ years of technical engineering experience with coding, or equivalent experience.
- Coding experience in languages including C, C++, C#, Java, JavaScript, or Python.
- Master’s degree with 12+ years of experience or bachelor’s degree with 15+ years of experience is preferred, or equivalent experience.
- Experience building data platforms for experimentation, metrics, and scorecards, including success metrics, guardrail metrics, and data quality, is preferred.
- Experience with Databricks-like platforms is preferred.
Benefits
- The typical U.S. base pay range is USD $165,600–$296,400 per year; a different range applies to specified San Francisco Bay Area and New York City metropolitan area locations.
- Certain roles may be eligible for benefits and other compensation.
- The position will remain open for a minimum of 5 days and accept applications on an ongoing basis until filled.
Tech Stack
Categories
Data Engineering
About Microsoft
Microsoft develops operating systems, productivity software, cloud services, developer tools, and consumer devices for individuals, enterprises, and governments. Its main products include Windows, Microsoft 365, Azure, Visual Studio/GitHub, Xbox, and LinkedIn; revenue comes from software subscriptions and licenses, cloud consumption, hardware sales, and advertising. Founded in 1975 and headquartered in Redmond, Washington, Microsoft is a public company traded on Nasdaq.