Principal Engineer (Big Data Platform)

Pinterest • Bachelor's Degree • Python • Java • Scala • 2 days ago
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Salary
$243k – $500k per year
Location
Hybrid (San Francisco, United States)
Seniority
Principal · 12+ years exp
Employment
Full-Time

Confirmed on the employer's own hiring board on Oct 9, 2026. First seen by Alion on Sep 11, 2026. Pinterest scores B on the Alion truth index.

Overview
Company
Impact
Profile match

Pinterest

Pinterest is a visual discovery and social platform where users save and share images and ideas, headquartered in San Francisco, California.
pinterest.co.uk • New York • San Francisco • Los Angeles • Berlin • Chicago • Video & Photo Sharing • Social Networks • 1001-5000 employees
Tech stack of Pinterest

Join Pinterest as a Principal Engineer to lead the development of our next-generation data infrastructure. You will work with cutting-edge big data and AI technologies, and have a significant impact on how data is processed and stored at scale.

Missions

  • Lead the strategy and technical direction of Pinterest’s data infrastructure for big data and AI applications.
  • Build and scale data infrastructure frameworks and infrastructure to process petabytes-scale datasets.
  • Provide thought leadership to the entire company on how data should be processed and stored more reliably, quickly and efficiently at scale.

Profil recherché

- Deep knowledge of big data / ML technologies (e.g. Flink, Spark, Presto, Kubernetes, Ray, PyTorch/TensorFlow)

- Exceptional collaboration skills with cross-functional partners, with the ability to navigate ambiguity, make tradeoffs, and keep stakeholders aligned on priorities and progress

- 12+ years of industry experience with a proven track record of technical excellence

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

- 8+ years of experience of building and support large scalable Kubernetes or big data platform

- Bachelor’s degree in Computer Science, a related technical field, or equivalent experience

- Experiences in Kubernetes and AWS technologies

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