Staff Software Engineer, Ads Measurement Products
Leads architecture of ads measurement platform, building large-scale data pipelines, ensuring reliability and rigor in lift studies. Requires 8+ years experience in data-intensive systems, Java/Python/SQL proficiency, and AI workflow transformation.
Team & Mission
The Measurement Products team helps advertisers measure the incremental impact of their Pinterest campaigns. They own core measurement products like Pinterest Conversion Lift (PCL) Studies and Brand Lift Studies, building the next-gen Measurement Hub for faster iteration and deeper integration.
Role Summary
Lead the architecture and technical direction of the measurement platform. Drive end-to-end platform evolution, partner with Product and Data Science, and ensure rigor, trust, and operational excellence in ads measurement.
What you’ll do:
- Own end-to-end architecture and delivery of features for lift measurement products, from design through reliability.
- Design, build, and optimize large-scale data pipelines for study setup, experiment execution, and results computation.
- Drive AI enablement through tooling, processes, coaching, and adoption for improved delivery speed and quality.
- Translate measurement methodology into production systems, partnering with Data Science.
- Build automated data validation, randomization checks, imbalance diagnostics, and continuous verification.
- Define SLAs, build monitoring and anomaly detection, and lead root-cause analysis.
- Mentor engineers and drive technical execution and collaboration.
What we’re looking for:
- BS+ in Computer Science or equivalent.
- 8+ years of professional software engineering experience in data-intensive systems.
- Strong proficiency in large-scale data pipelines using Java/Scala/Kotlin or Python, plus SQL.
- Experience designing reliable services and APIs, distributed systems, data modeling, performance optimization.
- Ability to transform engineering workflows using AI with measurable impact.
- Experience in AdTech, measurement products, or experimentation platforms.
- Knowledge of experimentation fundamentals.
- Experience with backtesting, controlled rollouts, and verification.
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