Software Engineer II

at  Pinterest

About Pinterest:
Millions of people across the world come to Pinterest to find new ideas every day. It’s where they get inspiration, dream about new possibilities and plan for what matters most. Our mission is to help those people find their inspiration and create a life they love. In your role, you’ll be challenged to take on work that upholds this mission and pushes Pinterest forward. You’ll grow as a person and leader in your field, all the while helping Pinners make their lives better in the positive corner of the internet.
Creating a life you love also means finding a career that celebrates the unique perspectives and experiences that you bring. As you read through the expectations of the position, consider how your skills and experiences may complement the responsibilities of the role. We encourage you to think through your relevant and transferable skills from prior experiences.
Our new progressive work model is called PinFlex, a term that’s uniquely Pinterest to describe our flexible approach to living and working. Visit our PinFlex landing page to learn more.
The Batch Processing Platform team is looking for a Software Engineer to help us build the next generation of big data platform and infrastructure at Pinterest. You’ll be working on some of the most exciting big data open source technologies (Spark, Kubernetes, etc.), at the scale of hundreds of petabytes of data to help Pinners discover and do what they love.

• Design and implement Fine Grained Access Control system for Pinterest’s big data platform (Spark, Flink, PyTorch, Ray and other ML/AI frameworks)
• Improve and customize the internals of open source Spark to meet our challenges at scale and actively participate in open source community
• Build and scale big data processing frameworks and infrastructure to process petabytes-scale datasets
• Work with internal customers on critical business use cases that rely on batch processing
• Provide thought leadership to the entire company on how data should be processed and stored more reliably, quickly and efficiently at scale