Senior Analytics Engineering Manager, Core Data Science

Pinterest; San Francisco (CA); Presencial; USD 177.000 - 365.000; Jornada completa

Descripción de la vacante

Pinterest is seeking an Analytics Engineering Manager II, Core Data Science to help improve the quality and velocity of data science. You will lead a high-performance team that partners with Core Data Science, creating rock-solid data foundations and tooling.

You will build self-service datasets, guide analytics tooling, and apply AI to accelerate insights while maintaining data integrity and governance across product and research teams.

Formación

• 6+ years of data experience in a fast-paced environment, including managing engineers.
• Fluent in SQL and a scripting language (Python or R) with complex data structures.
• Experience with ETL/ELT on large datasets and workflow orchestration.
• Proven track record delivering analytics solutions and cross-functional collaboration.
• Demonstrated use of AI to improve speed and quality in daily workflows.

Responsabilidades

• Build, inspire, and grow a high-performance analytics engineering team.
• Develop best practices for instrumentation and experimentation with product teams.
• Prototype AI tools and analysis pipelines to provide scalable insights.
• Use AI to accelerate analysis, prototyping, and automation with quality checks.
• Collaborate with Data Scientists and Engineers for self-service datasets and insights.
• Document tools/datasets and drive data quality and democratization strategy.
• Work cross-functionally to communicate insights with product, design, and research teams.

Conocimientos

SQL

Python

R

Data analysis

Team leadership

Communication

AI tooling

Educación

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

Herramientas

Airflow

Jupyter

Descripción del empleo

Pinterest is seeking an Analytics Engineering Manager II, Core Data Science to help improve the quality and velocity of data science. You will lead a high-performance team that partners with Core Data Science, creating rock-solid data foundations and tooling.

You will build self-service datasets, guide analytics tooling, and apply AI to accelerate insights while maintaining data integrity and governance across product and research teams.