Engineering Manager (Analytics Engineering, Core Data Science)

Pinterest; United States; On-site; USD 140,000 - 190,000; Full time

Job summary

Pinterest is seeking an Analytics Engineering Manager II, Core Data Science to elevate the quality and velocity of data science across the company. You will build robust data foundations, lead a diverse analytics engineering team, and partner closely with our Core Data Science organization to drive impactful insights.

You will shape people-facing and business-facing products by developing scalable tooling, instrumentation, and pipelines, while applying AI to accelerate analysis and maintain

Qualifications

• 6+ years of experience working with data in a fast-paced, data-driven environment, including experience managing engineers.
• Experience conducting workflow orchestration and ETL/ELT with large, complex datasets and DAG dependencies.
• Demonstrated ability to translate open-ended goals into defined, impactful objectives.
• High integrity and ownership, responsible for data sensitivity and final decisions.

Responsibilities

• Shape the future of Pinterest's people-facing and business-facing products by building rock-solid data foundations and tooling.
• Lead a high-performance analytics engineering team and partner with Core Data Science.
• Develop best practices for instrumentation and experimentation and communicate them to product engineering teams.
• Build and prototype AI tools and analysis pipelines to provide scalable insights and knowledge of data structures.

Skills

Analytics engineering

Leadership

SQL

Python

R

ETL/ELT

Data analysis

Education

Bachelor’s/Master’s/PhD in a quantitative field

Job description

• We are looking for an Analytics Engineering Manager II, Core Data Science to help improve the quality and velocity of data science at Pinterest
• You will shape the future of the people-facing and business-facing products we build by creating rock-solid data foundations and tooling, and by leading a high-performance team that partners closely with our Core Data Science organization
• 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

• 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
• Experience conducting workflow orchestration and ETL/ELT with huge, complicated datasets and handling DAG data dependencies
• 6+ years of experience working with data in a fast-paced, data-driven environment, including experience managing engineers
• High integrity and ownership: you protect sensitive data, avoid over-reliance on AI, and remain accountable for final decisions and deliverables
• 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
• Bachelor’s, Master’s, or PhD in a quantitative field such as Computer Science, Statistics, Mathematics, or a related discipline, or equivalent experience
• 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)
• 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
• Experience in automation, anomaly detection, or infrastructure/workflow optimization
• Experience building internal tooling to maximize engineering velocity