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Staff Software Engineer, Stream Processing Platform

Pinterest

Staff Software Engineer, Stream Processing Platform

Pinterest logo

Pinterest

full-time

Posted: December 12, 2025

Number of Vacancies: 1

Job Description

Responsibilities

  • Lead the strategy and technical direction of Pinterest’s Streaming platform
  • Improve and customize the internals of open source Flink to meet challenges at scale and actively participate in open source community
  • Build and scale stream processing frameworks and infrastructure to process millions of messages per second with terabytes of state
  • Work with internal customers on critical business use cases that rely on low latency stream processing
  • Provide thought leadership to the entire company on how real-time data should be processed and stored more reliably, quickly and efficiently at scale
  • Contribute to the team’s technical vision and long-term roadmap

Qualifications

  • 8+ years of industry experience with a proven track record of technical excellence
  • 5+ years of experience building and supporting large scalable big data infrastructure/platform
  • 4+ years of experience contributing to open-source Flink or streaming technologies
  • Deep knowledge of big data technologies (e.g. Flink, Spark, Hadoop, Parquet/ORC, Flink)
  • Experience in leading cross-team engineering efforts
  • Proficiency in one or more programming languages (Java, Scala, Python)
  • Experience in Kubernetes and AWS technologies
  • BS+ degree in a relevant field such as Computer Science or equivalent experience

Locations

  • Seattle, WA, US; Remote, US (Remote)

Salary

177,185 - 364,795 USD / yearly

Estimated Salary Rangemedium confidence

220,000 - 350,000 USD / yearly

Source: ai estimated

* This is an estimated range based on market data and may vary based on experience and qualifications.

Skills Required

  • Flinkintermediate
  • Kafkaintermediate
  • RocksDBintermediate
  • Sparkintermediate
  • Hadoopintermediate
  • Parquet/ORCintermediate
  • Kubernetesintermediate
  • AWSintermediate
  • Javaintermediate
  • Scalaintermediate
  • Pythonintermediate
  • Leading cross-team engineering effortsintermediate

Required Qualifications

  • 8+ years of industry experience with a proven track record of technical excellence (experience)
  • 5+ years of experience building and supporting large scalable big data infrastructure/platform (experience)
  • 4+ years of experience contributing to open-source Flink or streaming technologies (experience)
  • Deep knowledge of big data technologies (e.g. Flink, Spark, Hadoop, Parquet/ORC, Flink) (experience)
  • Experience in leading cross-team engineering efforts (experience)
  • Proficiency in one or more programming languages (Java, Scala, Python) (experience)
  • Experience in Kubernetes and AWS technologies (experience)
  • BS+ degree in a relevant field such as Computer Science or equivalent experience (experience)

Responsibilities

  • Lead the strategy and technical direction of Pinterest’s Streaming platform
  • Improve and customize the internals of open source Flink to meet challenges at scale and actively participate in open source community
  • Build and scale stream processing frameworks and infrastructure to process millions of messages per second with terabytes of state
  • Work with internal customers on critical business use cases that rely on low latency stream processing
  • Provide thought leadership to the entire company on how real-time data should be processed and stored more reliably, quickly and efficiently at scale
  • Contribute to the team’s technical vision and long-term roadmap

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Pinterest logo

Staff Software Engineer, Stream Processing Platform

Pinterest

Staff Software Engineer, Stream Processing Platform

Pinterest logo

Pinterest

full-time

Posted: December 12, 2025

Number of Vacancies: 1

Job Description

Responsibilities

  • Lead the strategy and technical direction of Pinterest’s Streaming platform
  • Improve and customize the internals of open source Flink to meet challenges at scale and actively participate in open source community
  • Build and scale stream processing frameworks and infrastructure to process millions of messages per second with terabytes of state
  • Work with internal customers on critical business use cases that rely on low latency stream processing
  • Provide thought leadership to the entire company on how real-time data should be processed and stored more reliably, quickly and efficiently at scale
  • Contribute to the team’s technical vision and long-term roadmap

Qualifications

  • 8+ years of industry experience with a proven track record of technical excellence
  • 5+ years of experience building and supporting large scalable big data infrastructure/platform
  • 4+ years of experience contributing to open-source Flink or streaming technologies
  • Deep knowledge of big data technologies (e.g. Flink, Spark, Hadoop, Parquet/ORC, Flink)
  • Experience in leading cross-team engineering efforts
  • Proficiency in one or more programming languages (Java, Scala, Python)
  • Experience in Kubernetes and AWS technologies
  • BS+ degree in a relevant field such as Computer Science or equivalent experience

Locations

  • Seattle, WA, US; Remote, US (Remote)

Salary

177,185 - 364,795 USD / yearly

Estimated Salary Rangemedium confidence

220,000 - 350,000 USD / yearly

Source: ai estimated

* This is an estimated range based on market data and may vary based on experience and qualifications.

Skills Required

  • Flinkintermediate
  • Kafkaintermediate
  • RocksDBintermediate
  • Sparkintermediate
  • Hadoopintermediate
  • Parquet/ORCintermediate
  • Kubernetesintermediate
  • AWSintermediate
  • Javaintermediate
  • Scalaintermediate
  • Pythonintermediate
  • Leading cross-team engineering effortsintermediate

Required Qualifications

  • 8+ years of industry experience with a proven track record of technical excellence (experience)
  • 5+ years of experience building and supporting large scalable big data infrastructure/platform (experience)
  • 4+ years of experience contributing to open-source Flink or streaming technologies (experience)
  • Deep knowledge of big data technologies (e.g. Flink, Spark, Hadoop, Parquet/ORC, Flink) (experience)
  • Experience in leading cross-team engineering efforts (experience)
  • Proficiency in one or more programming languages (Java, Scala, Python) (experience)
  • Experience in Kubernetes and AWS technologies (experience)
  • BS+ degree in a relevant field such as Computer Science or equivalent experience (experience)

Responsibilities

  • Lead the strategy and technical direction of Pinterest’s Streaming platform
  • Improve and customize the internals of open source Flink to meet challenges at scale and actively participate in open source community
  • Build and scale stream processing frameworks and infrastructure to process millions of messages per second with terabytes of state
  • Work with internal customers on critical business use cases that rely on low latency stream processing
  • Provide thought leadership to the entire company on how real-time data should be processed and stored more reliably, quickly and efficiently at scale
  • Contribute to the team’s technical vision and long-term roadmap

Target Your Resume for "Staff Software Engineer, Stream Processing Platform" , Pinterest

Get personalized recommendations to optimize your resume specifically for Staff Software Engineer, Stream Processing Platform. Takes only 15 seconds!

AI-powered keyword optimization
Skills matching & gap analysis
Experience alignment suggestions

Check Your ATS Score for "Staff Software Engineer, Stream Processing Platform" , Pinterest

Find out how well your resume matches this job's requirements. Get comprehensive analysis including ATS compatibility, keyword matching, skill gaps, and personalized recommendations.

ATS compatibility check
Keyword optimization analysis
Skill matching & gap identification
Format & readability score

Tags & Categories

Data EngineeringPinterestVisual DiscoverySocial MediaTech JobsData Engineering

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No related jobs found at the moment.