Sr. Staff Software Engineer - Big Data Platform

Sr Staff Software Engineer Big Data Platform

We’re looking for senior staff software engineers to help us build and lead the next generation of data infrastructure at Pinterest which powers mission critical big data and ML/AI applications. You’ll be working on some of the most exciting big data and ML/AI open source technologies (Kubernetes Spark Ray Flink etc.) at the scale of hundreds of petabytes of data to help Pinners discover and do what they love.

What you’ll do:

• Lead the strategy and technical direction of Pinterest’s data infrastructure for big data and ML/AI applications

• Build and scale data infra frameworks and infrastructure to process petabytes-scale datasets including job management resource management scheduling and remote shuffling

• Work with internal customers on critical business use cases that rely on big data

• Provide thought leadership to the entire company on how data should be processed and stored more reliably quickly and efficiently at scale

• Contribute to the team’s technical vision and long-term roadmap

What we’re looking for:

• 8+years of industry experience with a proven track record of technical excellence

• 5+ years of experience of building and support large scalable Kubernetes or big data platform

• Deep knowledge of infra / big data / ML technologies (e.g. Kubernetes Spark YuniKorn Flink Ray PyTorch/TensorFlow)

• Experience in leading cross-team engineering efforts

• Proficiency in one or more programming languages (Java Go Scala Python)

• Experiences in Kubernetes and AWS technologies

Relocation Statement:

• This position is not eligible for relocation assistance. Visit our PinFlex page to learn more about our working model.

In-Office Requirement Statement:

• We let the type of work you do guide the collaboration style. That means we're not always working in an office but we continue to gather for key moments of collaboration and connection.

• This role will need to be in the office for in-person collaboration 1-2 times / month and therefore can be situated anywhere in the country.

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