Analytics Engineering Manager - AI-Powered Data Science

Praxy; San Francisco (CA); Hybrid; USD 177,000 - 365,000; Full time

Job summary

Pinterest is seeking an Analytics Engineering Manager II, Core Data Science, to elevate data foundations and tooling across the organization. You will lead a diverse analytics engineering team, partner with product engineering, data science, and researchers to deliver scalable data solutions, and champion data quality and democratization.

In this role, you’ll build and instrument data pipelines, advance AI-assisted analysis, and drive self-service analytics while maintaining rigorous validation

Qualifications

• Fluent in SQL and a scripting language (Python or R).
• Experience with large, high-dimensional datasets and data modeling.
• Experience leading engineers and analytics teams.
• Ability to design and implement data instrumentation and experimentation.
• Proven track record turning insights into actionable product decisions.

Responsibilities

• Build and lead a high-performing analytics engineering team.
• Develop best practices for instrumentation, experimentation, and AI-assisted workflows.
• Prototype AI tools and pipelines to scale insights while ensuring data quality.
• Collaborate with Data Scientists and Engineers to enable self-service data assets.
• Document tools and datasets and drive data quality and democratization.

Skills

SQL

Python

R

ETL/ELT

Workflow orchestration

Data analysis

AI tooling

Cross-functional leadership

Education

Bachelor's, Master's, or PhD in a quantitative field

Job description

Pinterest is seeking an Analytics Engineering Manager II, Core Data Science, to elevate data foundations and tooling across the organization. You will lead a diverse analytics engineering team, partner with product engineering, data science, and researchers to deliver scalable data solutions, and champion data quality and democratization.

In this role, you’ll build and instrument data pipelines, advance AI-assisted analysis, and drive self-service analytics while maintaining rigorous validation