Staff Software Engineer (Analytics Engineering, Core Data Science)

Pinterest; United States; On-site; USD 150,000 - 190,000; Full time

Job summary

Pinterest seeks a Staff Software Engineer to improve the quality and velocity of data science by building rock-solid data foundations and tooling, and by leading a high-performance analytics engineering team that partners closely with our Core Data Science organization.

Lead by example and mentor a diverse team, develop best practices for instrumentation and experimentation, and build AI tools and analysis pipelines to deliver insights at scale while ensuring correctness and quality.

Qualifications

• 6+ years of experience working with data in a fast-paced, data-driven environment.
• Fluency in SQL and a scripting language (Python or R) with nested data structures.
• Experience building analytics solutions and data tooling for cross-functional teams.
• Ability to lead and mentor a diverse analytics engineering team.

Responsibilities

• Shape data foundations and tooling to improve data science quality and velocity.
• Lead a high-performance analytics engineering team partnering with Core Data Science.
• Develop best practices for instrumentation, experimentation, and AI tooling.
• Collaborate with product, design, and research to deliver self-service data and insights.

Skills

SQL

Python

R

Data manipulation

ETL/ELT

Window functions

Data analysis

DAG workflows

Education

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

Job description

• We are looking for a Staff Software Engineer 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
• Lead by example, and mentor a 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

High integrity and ownership: you protect sensitive data, avoid over-reliance on AI, and remain accountable for final decisions and deliverables6+ years of experience working with data in a fast-paced, data-driven environmentA 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 prioritiesExperience conducting workflow orchestration and ETL/ELT with huge, complicated datasets and handling DAG data dependenciesConsistent track record of supplying analytics solutions to existing teams, with the ability to take open-ended goals and scope them into defined, impactful objectivesAbility 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 techniquesBachelor’s, Master’s, or PhD in a quantitative field such as Computer Science, Statistics, Mathematics, or a related discipline, or equivalent experienceDemonstrated 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)Experience building internal tooling to maximize engineering velocityExperience in automation, anomaly detection, or infrastructure/workflow optimization