Staff Software Engineer- Growth Performance Marketing
Pinterest
| Company | |
| Category | Engineering |
| Location | San Francisco |
| Remote | Remote |
| Employment | Not stated |
| Level | Not stated |
| Salary | Not stated by the employer |
| Posted | 2 Jun 2026 |
| Last verified | 7 Aug 2026 |
| Source | Employer ATS (greenhouse) |
Description
About Pinterest:
Millions of people around the world come to our platform to find creative ideas, dream about new possibilities and plan for memories that will last a lifetime. At Pinterest, we’re on a mission to bring everyone the inspiration to create a life they love, and that starts with the people behind the product.
Discover a career where you ignite innovation for millions, transform passion into growth opportunities, celebrate each other’s unique experiences and embrace the flexibility to do your best work. Creating a career you love? It’s Possible.
At Pinterest, AI isn't just a feature, it's a powerful partner that augments our creativity and amplifies our impact, and we’re looking for candidates who are excited to be a part of that. To get a complete picture of your experience and abilities, we’ll explore your foundational skills and how you collaborate with AI.
Through our interview process, what matters most is that you can always explain your approach, showing us not just what you know, but how you think. You can read more about our AI interview philosophy and how we use AI in our recruiting process here . Pinterest's performance marketing engineering team owns the end-to-end systems that turn marketing dollars into measured user growth spanning attribution, bidding, budget optimization, and campaign management across major advertising platforms. This role is responsible for designing systems that scale across channels and adapt as privacy landscapes shift.
What you’ll do:
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
What we’re looking for:
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-drive