Senior Data Infrastructure Architect & Technical Leader

Meta; Menlo Park (CA); On-site; USD 250,000 - 320,000; Full time

Job summary

Meta is seeking a senior technical leader in Data Infrastructure to help shape the systems that power our data storage, processing, and analytics across Meta's products. This role will set technical direction for large-scale data platforms and drive architecture used by thousands of engineers.

The ideal candidate has deep experience building foundational data systems, guiding multi-year roadmaps, and advancing reliable, ethical AI practices in complex environments.

Qualifications

• 12+ years of experience in systems software engineering
• Experience architecting global-scale critical systems
• Experience leading multi-year technical strategy and roadmaps
• Experience identifying systemic bugs and reliability issues
• Experience influencing engineering culture across large organizations
• Demonstrated ability to integrate AI tools to optimize workflows
• Active focus on responsible AI practices

Responsibilities

• Set technical direction for large, cross-cutting data-infrastructure efforts
• Drive architecture for systems used by thousands of engineers
• Custodian of Meta's data systems supporting Frontier Models, ML, analytics, and reliability
• Lead cross-organizational alignment and execute through ambiguity
• Define engineering standards and practices adopted broadly across teams

Skills

Distributed systems

Large-scale data platforms

Cross-functional leadership

System reliability

AI safety & ethics

Performance optimization

Incident response

Prompt/context engineering

Education

Bachelor's degree in CS/CE or equivalent

Tools

Open source data infra tools

Job description

Meta is seeking a senior technical leader in Data Infrastructure to help shape the systems that power our data storage, processing, and analytics across Meta's products. This role will set technical direction for large-scale data platforms and drive architecture used by thousands of engineers.

The ideal candidate has deep experience building foundational data systems, guiding multi-year roadmaps, and advancing reliable, ethical AI practices in complex environments.