P

Pinterest

Runs an app for finding and saving visual ideas

Software Engineer 2 - Data Analytics and Engineering

Data EngineeringConfirmed live in the last 24 hours
Full-time

About the Job

Requirements

  • A 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.
  • Ability to critically evaluate and verify AI-assisted work through testing, data validation, source-checking, or peer review.
  • Ability to 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, or Mathematics, or equivalent experience.

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, applying judgment and verification to ensure correctness, quality, and responsible use.

About the Company

Pinterest

Runs an app for finding and saving visual ideas

Pinterest runs a visual search and discovery app where people look for ideas in areas like cooking, home decor, fashion, and travel, then save the images they like to themed collections called boards. In 2012 it became the fastest standalone website to reach 10 million monthly US visitors, according to measurement firm comScore. Each saved image, called a Pin, links back to its source, such as a recipe or a product page, and people search with words or with a photo to find similar ideas and things to buy. Brands pay to show ads among Pins in feeds and search results, and Pinterest also sells ads on streaming TV. It launched in 2010 and is based in San Francisco, California.

Company size
5,001-10,000
Company stage
IPO
Headquarters
San Francisco, CA
Founded
2010

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