Staff Software Engineer, Conversion Data Privacy

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, finegrained access controls, centralized privacy rules enforcement, and deidentification pipelines for conversion data. Our mission is to make conversion data privacypreserving by default-centralized, deidentified, 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 deidentification for ads reporting. You'll own the endtoend design and evolution of privacycritical 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, deidentification, deletion, and privacy rules enforcement, driving toward a centralized, deidentifiedbydefault, automated privacy platform for monetization.
• Design and evolve core privacy infrastructure including controlled environments for sensitive data, finegrained authorization and policy enforcement, and a central policy repository that consistently governs access across major data platforms and query engines.
• Own deidentification pipelines for ads reporting endtoend-from separating sensitive and nonsensitive data, applying deidentification techniques and transformations, and generating privacypreserving 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 selfservice 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., deidentification quality, optout metrics, data leakages), leading incident response, and developing performant deletion and leakagehandling workflows that meet regulatory and audit requirements.
• Partner crossfunctionally with ads, data, product, legal, and infrastructure stakeholders to translate legal/privacy requirements into technical designs, make clear tradeoffs 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 privacysensitive areas, and establish best practices and documentation for privacybydesign, deidentification, and largescale data systems.

What we're looking for:

• BS+ in Computer Science (or related field) or equivalent practical experience.
• 8+ years of professional software engineering experience, with a focus on largescale data systems or distributed systems.
• Strong proficiency building and operating data pipelines and services using Java/Scala/Kotlin or Python, plus SQL; experience with modern big data ecosystems is a plus.
• Experience designing secure, reliable systems and APIs, with solid grounding in data modeling, access control, and performance optimization.
• Meaningful experience in at least one of: privacypreserving data systems (e.g., deidentification, kanonymity), ads measurement/attribution, or largescale analytics/experimentation platforms.
• Proven ability to drive crossteam technical initiatives from design through rollout, working closely with product, data science, and nonengineering partners (e.g., Legal, Compliance).
• Strong communication and leadership skills, with a track record of mentoring engineers, raising engineering standards, and making sound decisions in ambiguous, highimpact problem spaces.

In-Office Requirement Statement:

• We recognize that the ideal environment for work is situational and may differ across departments. What this looks like day-to-day can vary based on the needs of each organization or role.

Relocation Statement:

• This position is not eligible for relocation assistance. Visit our PinFlex page to learn more about our working model.

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