[Remote] Manager II, Engineering- Analytics Engineering, Core Data Science

Note: The job is a remote job and is open to candidates in USA. Pinterest is a platform that helps people discover creative ideas and plan meaningful experiences. The company is seeking an Analytics Engineering Manager II to lead a high-performance team, improve data science quality and velocity, and build reliable data foundations, tooling, analytics pipelines, and self-service data processes.

Responsibilities

• 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 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

Skills

• 6+ years of experience working with data in a fast-paced, data-driven environment, including experience managing engineers
• 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

Benefits

• The position is also eligible for equity.
• Flexibility to do your best work.
• This role will need to be in the office for in-person collaboration 1-2 times/month and therefore can be situated anywhere in the country.

Company Overview

Company H1B Sponsorship