Staff Software Engineer, Ads Measurement Products

Pinterest Pinterest · Consumer · San Francisco, CA · Monetization

Staff Software Engineer for Pinterest's Ads Measurement Products team. This role focuses on leading the architecture and technical direction of the measurement platform, including data pipelines, services, and AI enablement. The engineer will partner with Product and Data Science to ensure rigor, trust, and operational excellence in ads measurement.

What you'd actually do

  1. Own end‑to‑end architecture and delivery of features for lift measurement products, from design and implementation through rollout and ongoing reliability.
  2. Design, build, and optimize large‑scale data pipelines that power study setup, experiment execution, and results computation.
  3. Drive AI enablement across the team by building the supporting tooling and processes (CI checks, test strategy, templates), coaching engineers, and ensuring adoption results in sustained improvements to delivery speed and system quality.
  4. Translate measurement methodology into production systems: partner with Data Science to operationalize study design requirements into pipelines, services, tooling, and guardrails.
  5. Build “rigor by default” mechanisms: automated data validation, randomization/holdout integrity checks, imbalance diagnostics, and continuous verification/backtesting.

Skills

Required

  • BS+ in Computer Science (or related field) or equivalent practical experience.
  • 8+ years of professional software engineering experience, with a focus on data‑intensive systems.
  • Strong proficiency building and operating large‑scale data pipelines (batch and/or streaming) using Java/Scala/Kotlin or Python, plus SQL.
  • Experience designing reliable services and APIs, with solid foundations in distributed systems, data modeling, and performance optimization.
  • Demonstrated ability to transform a team’s engineering workflow using AI—from pilot to broad adoption—through tooling, enablement, and change leadership, with clear metrics (cycle time, defect rate, on-call load, incident rate).
  • Experience in AdTech and measurement products (e.g., conversion lift, brand lift) or adjacent experimentation/analytics platforms.
  • Working knowledge of experimentation and causal measurement fundamentals (randomization, holdouts, confounders, significance, power).
  • Practical experience with backtesting, controlled rollouts, and continuous verification for correctness in measurement/analytics systems.
  • Demonstrated ability to lead large cross‑functional initiatives, drive alignment, and deliver measurable impact through technical leadership.

What the JD emphasized

  • Demonstrated ability to transform a team’s engineering workflow using AI—from pilot to broad adoption—through tooling, enablement, and change leadership, with clear metrics (cycle time, defect rate, on-call load, incident rate).