Staff Software, Engineering – Analytics Engineering, Core Data Science

Pinterest is a platform that helps people discover creative ideas and plan for the future. The company is seeking a Staff Software Engineer to improve the quality and velocity of data science by building data foundations, analytics tooling, and analysis pipelines while leading a team of analytics engineers. The role partners with data scientists, engineers, and cross-functional teams to enable self-service insights, improve data quality, and support experimentation.

Responsibilities:

• Lead by example, and mentor a diverse team of analytics engineers with an inclusive culture
• Develop best practices for instrumentation and experimentation and communicate those to product engineering teams
• Build and prototype AI tools and analysis pipelines iteratively to provide insights at scale while developing comprehensive knowledge of data structures and metrics, advocating for changes where needed
• Use AI to accelerate analysis, prototyping, and iteration—drafting pipelines, exploring approaches, and automating repeatable documentation and QA—while applying judgment and verification to ensure correctness and quality
• Work closely with Data Scientists and Engineers to build tools and processes that enable self-service of key datasets, insights, and metric investigations
• Contribute to comprehensive documentation of tools and datasets, and drive the strategy for better data quality and data democratization within Pinterest
• Work cross-functionally to build and communicate key insights, collaborating with product managers, engineers, designers, and researchers to help build the next experiences on Pinterest

Requirements:

• 6+ years of experience working with data in a fast-paced, data-driven environment
• Ability to manipulate large data sets with high dimensionality and complexity; fluency in SQL (or other database languages) and a scripting language (Python or R), including nested data structure manipulation, windowing functions, query optimization, and data partitioning techniques
• Experience conducting workflow orchestration and ETL/ELT with huge, complicated datasets and handling DAG data dependencies
• Consistent track record of supplying analytics solutions to existing teams, with the ability to take open-ended goals and scope them into defined, impactful objectives
• A team player able to partner with cross-functional leadership to quickly turn insights into actions, and an accountable operator who proactively identifies project opportunities amid competing priorities
• Demonstrated ability to use AI to improve speed and quality in your day-to-day workflow, with a strong track record of critical evaluation and verification of AI-assisted work (testing, source-checking, data validation, 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, Master's, or PhD in a quantitative field such as Computer Science, Statistics, Mathematics, or a related discipline, or equivalent experience
• Experience in automation, anomaly detection, or infrastructure/workflow optimization
• Experience building internal tooling to maximize engineering velocity