Staff Software, Engineering – Analytics Engineering, Core Data Science
Pinterest · San Francisco, CA, US; Remote, US
About this role
**About Pinterest** Millions of people around the world come to Pinterest to find creative ideas, dream about new possibilities, and plan for memories that will last a lifetime. At Pinterest, our mission is to bring everyone the inspiration to create a life they love—powered by the people behind the product. Pinterest uses AI as a powerful partner to augment creativity and amplify impact. In interviews, we focus on how you think and how you explain your approach. --- **Role: Staff Software Engineer (Analytics Engineering, Core Data Science)** Help improve the quality and velocity of data science at Pinterest. You’ll shape future people-facing and business-facing products by building rock-solid data foundations and tooling, and by leading a high-performance team that partners closely with Core Data Science. --- **What you’ll do** - Lead by example and mentor a diverse team of analytics engineers with an inclusive culture. - Develop best practices for instrumentation and experimentation, and communicate them to product engineering teams. - Build and prototype AI tools and analysis pipelines iteratively to deliver insights at scale, while deepening knowledge of data structures and metrics (and advocating for changes when needed). - Use AI to accelerate analysis, prototyping, and iteration-drafting pipelines—automating repeatable documentation and QA while applying judgment and verification to ensure correctness and quality. - Partner 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 strategy for better data quality and data democratization. - Work cross-functionally to build and communicate key insights with product managers, engineers, designers, and researchers. --- **What we’re looking for** - 6+ years of experience working with data in a fast-paced, data-driven environment. - Strong ability to manipulate large, high-dimensional datasets; fluency in SQL (or other database languages) and a scripting language (Python or R), including nested data manipulation, window functions, query optimization, and data partitioning. - Experience with workflow orchestration and ETL/ELT on huge, complex datasets, including DAG dependency handling. - Proven track record delivering analytics solutions; ability to take open-ended goals and scope them into defined, impactful objectives. - Team player who can partner with cross-functional leadership to turn insights into actions; proactive, accountable operator. - Demonstrated ability to use AI to improve speed and quality, with strong critical evaluation and verification (testing, source-checking, data validation, peer review). - High integrity and ownership: 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 (e.g., CS, Statistics, Math) or equivalent experience. **Desired (not required)** - Experience in automation, anomaly detection, or infrastructure/workflow optimization. - Experience building internal tooling to maximize engineering velocity. --- **Location / Work model** - **Relocation:** Not eligible for relocation assistance. - **In-office requirement:** In-person collaboration 1–2 times/month; role can be situated anywhere in the country. - Tags: **#LI-REMOTE**, **#LI-AG8** --- **Compensation (US based appl
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