Pinterest

Sr. Staff Software Engineer, Big Data Platform

Pinterest$162K — $195K *
Enterprise Technology
8 - 10 years of experience
Job Overview by Ladders

Qualifications

  • 10+ years of industry experience in software engineering
  • 5+ years experience building scalable Kubernetes or big data platforms
  • Deep knowledge of big data/ML technologies such as Flink, Spark, and Kubernetes
  • Proficient in programming languages like Java, Go, Scala, or Python
  • Experience with AWS technologies
  • Strong collaboration skills and ability to manage stakeholder expectations
  • Bachelor’s degree in Computer Science or related field

Responsibilities

  • Lead strategy and technical direction for Pinterest's data infrastructure
  • Build and scale data frameworks to process massive datasets
  • Collaborate with internal customers on critical big data use cases
  • Provide thought leadership on efficient data processing and storage
  • Contribute to the technical vision and long-term roadmap of the team

Benefits

  • In-office collaboration required only 1-2 times a quarter
  • Work remotely with flexibility in location
  • Opportunity to work with cutting-edge open source technologies
  • Engage in high-impact big data and AI projects
  • Foster a culture of collaboration and innovation
Full Job Description
We9re 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. You9ll 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 you9ll do: - Lead the strategy and technical direction of Pinterest9s 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 team9s technical vision and long-term roadmap What we9re 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. - Bachelor9s 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 we9re 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.

About Pinterest

Pinterest is a social media platform that allows users to discover and save ideas for recipes, home decor, fashion, and more. The company was founded in 2010 and is headquartered in San Francisco, California. Pinterest has over 400 million monthly active users and is available in over 30 languages. The company's mission is to help people discover and do what they love.
Learn more about Pinterest
Size
3,225 employees
Market Cap
$16 billion
Industry
Net Income
-$128.3 million
Founded
2009
5 Year Trend
+53.9%
Revenue
$1.6 billion
NASDAQ

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