Software Engineer, Ads Conversion Measurement

Details

The Monetization team is a cross-functional group working across engineering, product, research, and design to build foundational systems for privacy-preserving monetization products, including next-generation ads experiences. The team operates in a greenfield environment and partners closely with Product, Design, and Research to bring research breakthroughs into real-world systems at global scale.

The role involves building measurement systems that connect ad interactions to meaningful advertiser outcomes while protecting user privacy. The engineer will design infrastructure for conversion signals, attribution, reporting, and feedback loops across ads products. The work spans event collection and normalization, deduplication and matching, attribution and modeled measurement, privacy-safe aggregation, reporting, and high-quality labels for ads optimization.

Responsibilities

• Design and build reliable conversion-event collection and processing systems across pixels, SDKs, server-side APIs, app events, offline uploads, and advertiser integrations.
• Build attribution and measurement infrastructure for observed and modeled conversions, attribution windows, deduplication, delayed events, and signal-loss mitigation.
• Develop privacy-preserving identity, matching, aggregation, and reporting systems under strict privacy constraints.
• Create data-quality systems to detect missing, duplicated, malformed, out-of-order, fraudulent, or misconfigured conversion signals.
• Build scalable advertiser reporting and diagnostics for conversions, cost per action, return on ad spend, funnel performance, and measurement health.
• Partner with Ads ML to deliver trustworthy conversion labels and feedback loops for ranking, bidding, targeting, and budget optimization.
• Develop experimentation and incremental capabilities, including holdouts, lift studies, and causal measurement foundations.
• Define the technical strategy and roadmap for conversion measurement across the ads delivery stack.
• Operate systems with high engineering rigor through testing, observability, privacy reviews, incident response, and operational best practices.
• Work closely with Ads Delivery, Ads ML, Product, Research, Privacy, Data Science, Design, and advertiser-facing teams.

Requirements

• 10+ years of experience building and operating large-scale distributed data or backend systems, ideally in ads measurement, attribution, analytics, marketplaces, experimentation, or adjacent domains.
• Understanding of conversion-event pipelines, attribution, deduplication, identity and matching, reporting, or downstream optimization signals.
• Experience designing privacy-safe measurement systems, including aggregation, consent handling, modeled conversions, clean-room patterns, or privacy-preserving APIs.
• Ability to reason about data correctness, delayed and out-of-order events, schema evolution, reconciliation, and internal-versus-external metric discrepancies.
• Experience building high-throughput batch or streaming systems and making tradeoffs across latency, reliability, cost, and maintainability.
• Comfort partnering with machine learning and data science teams on labels, model inputs, experimentation, and causal measurement.
• Holistic understanding of architecture, product semantics, data quality, observability, privacy, and advertiser trust.
• Ability to define technical direction in an ambiguous 0-to-1 environment and independently drive complex work across teams.
• Clear communication and sound technical decision-making grounded in user value, system health, measurement credibility, and long-term product direction.

Benefits

• Base salary of $293,000–$385,000 per year, plus equity.
• Medical, dental, and vision insurance, with employer contributions to Health Savings Accounts.
• Pre-tax accounts for health, dependent care, and commuter expenses.
• 401(k) retirement plan with employer match.
• Paid parental, medical, and caregiver leave.
• Paid time off, company holidays, office closures, and sick or safe time.
• Mental health and wellness support.
• Employer-paid basic life and disability coverage.
• Annual learning and development stipend.
• Daily office meals and eligible meal delivery credits.
• Relocation support for eligible employees.
• Additional benefits may include charitable donation matching and wellness stipends.