Lead the technical roadmap for the performance marketing platform, defining the highest-impact investments across attribution, bidding, budget optimization, and campaign management
Drive hands-on engineering across ad platform integrations, event pipelines, and production systems that deploy and measure marketing spend
Design and evolve the measurement stack — attribution models, conversion signal collection, incrementality methodology, and privacy-resilient approaches as platform signals degrade
Develop systems that automate and optimize bidding strategies and campaign experimentation at scale
Drive cross-team technical initiatives with ads platform, data warehouse, and mobile teams — authoring design documents and building alignment across engineering orgs
Own system reliability and operational health for spend-critical systems where downtime or bugs have direct financial impact
Collaborate with marketing, data science, and product partners to identify growth opportunities and turn them into engineered solutions
Mentor and develop engineers on the team, establishing technical best practices and raising the bar on system design
Use AI to accelerate your own work—across exploration, drafting, analysis, and synthesis—while maintaining strong judgment, rigorous validation, and accountability for outcomes

7+ years of experience building and shipping backend systems, with hands-on experience supporting performance marketing
Strong understanding of paid media platforms — Google Ads, Meta, TikTok, Snap, or similar — and the operational realities of integrating with their APIs at scale
Deep understanding of attribution methodologies (last click, multi-touch, SKAN, probabilistic vs. deterministic), incrementality testing, and conversion optimization, with hands-on experience integrating mobile measurement partners (AppsFlyer, Adjust, Singular, or similar) across mobile clients and server-side APIs
Experience with near real-time systems for bidding, budget optimization, and conversion event delivery — you understand the mechanics well enough to evolve existing systems and propose improvements
Strong proficiency building and operating data pipelines and services using Python or Java/Scala, plus SQL; experience with modern big data ecosystems is a plus
Strong systems design skills across distributed systems, event-driven architectures, and service-oriented backends
Familiarity with ML infrastructure concepts and ability to build systems that support ML workloads
Demonstrated ability to use AI to accelerate your workflow while maintaining high standards for verification, data integrity, and ownership of final outputs
Bachelor’s degree in a relevant field such as Computer Science, or equivalent experience.

Information regarding the culture at Pinterest and benefits available for this position can be found here.

Staff Software Engineer – Growth Performance Marketing

Key skills