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Staff

Staff Software Engineer, Conversion Data Privacy

Confirmed live in the last 24 hours

Pinterest

Pinterest

Compensation

$177,185 - $364,795/year

San Francisco, CA, US; Remote, US
Remote
Posted March 27, 2026

Job 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.

Team & Mission

The Privacy & Conversion Data team is responsible for how the company safely and compliantly uses conversion data to power monetization. We build and operate the core privacy infrastructure behind ads reporting and optimization, including controlled data environments, fine‑grained access controls, centralized privacy rules enforcement, and de‑identification pipelines for conversion data. Our mission is to make conversion data privacy‑preserving by default—centralized, de‑identified, auditable, and easy for teams to use, while maintaining high utility for advertisers and staying ahead of an evolving global regulatory landscape.

 

Role Summary

We’re seeking a Staff Engineer to lead the architecture and technical direction for the conversion data privacy platform, spanning both core Conversion Data systems and de‑identification for ads reporting. You’ll own the end‑to‑end design and evolution of privacy‑critical pipelines and services, partner closely with Product, Data Science, Legal, and infrastructure teams, and set the technical bar for how we use conversion data safely at scale.

 

What you’ll do:

  • Lead the technical strategy and architecture for conversion data privacy across access controls, de‑identification, deletion, and privacy rules enforcement, driving toward a centralized, de‑identified‑by‑default, automated privacy platform for monetization.
  • Design and evolve core privacy infrastructure including controlled environments for sensitive data, fine‑grained authorization and policy enforcement, and a central policy repository that consistently governs access across major data platforms and query engines.
  • Own de‑identification pipelines for ads reporting end‑to‑end—from separating sensitive and non‑sensitive data, applying de‑identification techniques and transformations, and generating privacy‑preserving datasets, to validating data utility and feeding reporting and analytics surfaces.
  • Build and improve privacy frameworks and tooling (for both online and offline workflows) that make safe, compliant conversion data usage simple and self‑service for downstream teams, reducing onboarding friction for new datasets, restrictions, and use cases.
  • Drive operational excellence and compliance by defining SLAs, building robust monitoring and alerting (e.g., de‑identification quality, opt‑out metrics, data leakages), leading incident response, and developing performant deletion and leakage‑handling workflows that meet regulatory and audit requirements.
  • Partner cross‑functionally with ads, data, product, legal, and infrastructure stakeholders to translate legal/privacy requirements into technical designs, make clear trade‑offs between privacy and utility, and drive alignment on roadmaps, launches, and policy changes that impact advertisers and users.
  • Mentor and uplevel engineers across multiple teams, lead critical design and code reviews in privacy‑sensitive areas, and establish best practices and documentation for privacy‑by‑design, de‑identification, and large‑scale data systems.

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