Manager II, 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: Analytics Engineering Manager II, Core Data Science** Help improve the quality and velocity of data science at Pinterest. You’ll shape the future of 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 the Core Data Science organization. --- **What you’ll do** - Build, inspire, and grow a high-performance, 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. - 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, including experience managing engineers. - 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 data dependencies. - Proven track record delivering analytics solutions; ability to take open-ended goals and scope them into defined, impactful objectives. - Strong team player who can partner cross-functionally to turn insights into actions; accountable and proactive about identifying opportunities amid competing priorities. - Demonstrated ability to use AI to improve speed and quality, with a strong record of 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., Computer Science, Statistics, Mathematics) or equivalent experience. **Desired but not required** - Experience in automation, anomaly detection, or infrastructure/workflow optimization. - Experience building internal tooling to maximize engineering velocity. --- **Relocation & In-Office Requirements** - **Relocation:** This position is **not** eligible for relocation assistance. - **In-office:** In-person collaboration **1–2 times/mont
Listing freshness
CronJobs last confirmed this listing 1h ago. If its source stops confirming the opening for seven days, this page is removed from active inventory.