This role pays more than
83%
of similar roles. Most pay
$164,362–$246,150
— the shaded band above.
At the midpoint, this role pays about
$271k
versus about
$205k
for comparable roles.
Based on 240 similar postings.
Employer
About Pinterest
Pinterest is a visual discovery and inspiration platform where people find ideas for home, style, recipes, and more. It serves hundreds of millions of users worldwide through its image and video pinboard product.
Pinterest currently has
48 open roles
on FindRole.
Listed pay typically runs
$177,185–$339,078
across 42 roles with salary data.
Manager II, Engineering- Analytics Engineering, Core Data Science leads a high-performance team within the Core Data Science organization to improve data science quality and velocity. The manager builds rock-solid data foundations, develops instrumentation and experimentation best practices, and creates tools for self-service of key datasets and metric investigations. Day-to-day responsibilities include building analysis pipelines, drafting documentation, and collaborating cross-functionally with product managers and engineers to drive data democratization. The role requires expertise in SQL, Python or R, and workflow orchestration for complex ETL/ELT processes involving large, high-dimensional datasets. Candidates must demonstrate the ability to use AI tools to accelerate prototyping while ensuring rigorous verification of results. This position addresses the technical challenge of providing scalable insights and infrastructure to support both people-facing and business-facing products through robust data structures and automated reporting systems.
What does a Engineering Manager earn in California?
Median $290250 from 62 postings across 17 companies.
Lead and grow a high-performing team of analytics engineers within an inclusive culture.
Develop best practices for instrumentation and experimentation to communicate with product engineering teams.
Build and prototype AI tools and analysis pipelines to provide insights at scale.
Use AI to automate documentation, accelerate prototyping, and streamline repetitive data tasks.
Partner with Data Scientists and Engineers to build self-service tools for datasets and metric investigations.
Drive the strategy for data quality, democratization, and comprehensive documentation of internal tools.
Collaborate cross-functionally with product managers and designers to translate insights into new features.
What we're looking for
6+ years of experience working with data in a fast-paced environment, including experience managing engineers.
Ability to manipulate large, complex datasets using SQL and a scripting language like Python or R.
Experience conducting workflow orchestration and ETL/ELT with huge datasets and handling DAG data dependencies.
Proven track record of providing analytics solutions and scoping open-ended goals into defined objectives.
Demonstrated ability to use AI to improve workflow speed while ensuring quality through critical evaluation and verification.
Bachelor's, Master's, or PhD in a quantitative field such as Computer Science, Statistics, Mathematics, or related discipline, or equivalent experience.
Experience in automation, anomaly detection, or infrastructure/workflow optimization (preferred).
Experience building internal tooling to maximize engineering velocity (preferred).