Sr. Staff Software Engineer, Big Data Platform

We’re looking for a senior staff software engineer to lead the next generation of data infrastructure at Pinterest which powers mission critical big data and AI applications. You’ll be working on some of the most exciting big data and AI open source technologies (Flink, Spark, Kubernetes, etc.), at the scale of exabytes 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 AI applications
• Build and scale data infra frameworks and infrastructure to process petabytes-scale datasets, including compute engines, 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:

• 10+ 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 big data / ML technologies (e.g. Flink, Spark, Presto, Kubernetes, Ray, PyTorch/TensorFlow)
• Proficiency in one or more programming languages (Java, Go, Scala, Python)
• Experiences in Kubernetes and AWS technologies
• Exceptional collaboration skills with cross-functional partners, with the ability to navigate ambiguity, make tradeoffs, and keep stakeholders aligned on priorities and progress.
• Bachelor’s degree in Computer Science, a related technical field, or equivalent experience.

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/quarter and therefore can be situated anywhere in the country.

Relocation Statement:

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