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Dice
Posted 13 days agoVerified live 1d ago

Software Engineer II, Data Analytics & Engineering

Brief overview

Remote
UndergradOr in progress
$124k–$255k/yrStated range
2+ yrsMinimum
SQLPythonRData StructuresQuery OptimizationData PartitioningWorkflow OrchestrationETL/ELT PipelinesData ValidationTestingArtificial Intelligence

About the company

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Job description

Summary

Pinterest is a platform that helps people discover creative ideas and plan for the future. The Software Engineer II, Data Analytics and Engineering will build scalable data foundations, analytics tooling, and analysis pipelines that improve data quality and enable trusted, self-service access to datasets, insights, and metrics. The role also partners with cross-functional teams to support experimentation, product development, and responsible AI-assisted analysis.

Responsibilities

  • Develop and document practical instrumentation and experimentation standards, then partner with product engineering teams to apply them to priority product development work
  • Build and improve scalable analysis pipelines and tooling that produce reliable insights at scale and strengthen understanding of key data structures and metrics
  • Create tools and processes that enable Data Scientists and Engineers to independently access trusted datasets, insights and metric definitions
  • Identify data quality and discoverability gaps, advocate for targeted improvements and contribute to reliable, well-governed data practices
  • Maintain clear documentation for tools, datasets, metrics and operating practices to make team data assets easier to use
  • Partner with Product, Engineering, Data Science, Data Engineering and Business Intelligence teams to communicate actionable insights and inform product improvements
  • Use AI to accelerate analysis, prototyping and iteration, while applying judgment and verification to ensure correctness, quality and responsible use

Skills

  • Minimum of 2 years of experience delivering analytics engineering or data solutions in a fast-paced, data-driven environment
  • Experience using SQL and Python, R or a comparable programming language to work with large, high-dimensional datasets, including nested data structures, window functions, query optimization and data partitioning
  • Experience building and operating data workflows, including workflow orchestration, ETL/ELT pipelines and DAG dependencies across complex datasets
  • Experience translating open-ended partner needs into clear, impactful technical objectives and collaborating across Product, Engineering, Data Science, Data Engineering and Business Intelligence teams
  • Demonstrated ability to use AI to improve speed and quality in day-to-day engineering workflows
  • Strong track record of critically evaluating and verifying AI-assisted work through testing, data validation, source-checking or peer review
  • High integrity and ownership: you protect sensitive data, avoid over-reliance on AI and remain accountable for final decisions and deliverables
  • Bachelor's degree in a relevant field such as Computer Science, Statistics, Mathematics or a related discipline, or equivalent experience
  • This position is not eligible for relocation assistance. Visit our PinFlex page to learn more about our working model
  • This role will need to be in the office for in-person collaboration 1-2 times per month and therefore can be situated anywhere in the country
  • US based applicants only

Qualifications

Must Haves

  • Minimum of 2 years of experience delivering analytics engineering or data solutions in a fast-paced, data-driven environment
  • Experience using SQL and Python, R or a comparable programming language to work with large, high-dimensional datasets, including nested data structures, window functions, query optimization and data partitioning
  • Experience building and operating data workflows, including workflow orchestration, ETL/ELT pipelines and DAG dependencies across complex datasets
  • Experience translating open-ended partner needs into clear, impactful technical objectives and collaborating across Product, Engineering, Data Science, Data Engineering and Business Intelligence teams
  • Demonstrated ability to use AI to improve speed and quality in day-to-day engineering workflows
  • Strong track record of critically evaluating and verifying AI-assisted work through testing, data validation, source-checking or peer review
  • High integrity and ownership: you protect sensitive data, avoid over-reliance on AI and remain accountable for final decisions and deliverables
  • Bachelor's degree in a relevant field such as Computer Science, Statistics, Mathematics or a related discipline, or equivalent experience
  • This position is not eligible for relocation assistance. Visit our PinFlex page to learn more about our working model
  • This role will need to be in the office for in-person collaboration 1-2 times per month and therefore can be situated anywhere in the country
  • US based applicants only

Benefits

  • The position is also eligible for equity.
  • This role can be situated anywhere in the country, with in-person collaboration required 1-2 times per month.

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