Senior Performance Advertising Engineer

Location: Remote OR Hybrid (Redwood City or NYC) About the Role: We are seeking a results-oriented Senior Performance Advertising Engineer to own and drive the optimization of our buyer-side and performance marketing systems. In this role, you will be directly responsible for designing algorithms, building data systems, and refining optimization loops that drive Return on Ad Spend (ROAS) for our Advertisers and Agencies. You will own the technical architecture and end-to-end evaluation, implementation, and scaling of robust data pipelines for attribution data. This position spans our complete omnichannel environment, requiring expert-level performance engine development across Mobile App (including privacy-aware frameworks like SKAdNetwork and Privacy Sandbox), Video, Connected TV (CTV), and Desktop environments. What You'll Do: ROAS Optimization & Algorithmic Design: Develop, benchmark, and deploy real-time bidding (RTB) algorithms, pacing controls, and predictive models aimed squarely at maximizing ROAS and conversion tracking across all screens (CTV, Mobile App, Video, and Desktop). Attribution Data Pipelines: Design, evaluate, and implement scalable, low-latency streaming and batch data pipelines that ingest, validate, and process complex conversion and multi-touch attribution (MTA) datasets. Omnichannel Execution: Advance PubMatic’s performance capabilities across specific programmatic formats: - Mobile: Build robust mechanisms that thrive within SKAdNetwork, Attribution API, and Android Privacy Sandbox constraints. - CTV & Video: Implement precise cross-device graph integrations, household-level frequency capping, and server-to-server attribution systems. - Desktop: Innovate alternative identity framework integrations (e.g., UID2, LiveRamp ATS) to sustain high attribution fidelity post-third-party cookies. Data Pipeline Evaluation: Constantly audit existing data ingestion points for architectural flaws, data loss, or systemic latencies that negatively skew attribution accuracy and campaign performance. Scalable Systems Engineering: Write high-performance, low-latency, and memory-efficient code (Python, Go, Java, or C++) matching our ultra-scaled backend layer that processes trillions of monthly events. Who You Are: Education: Bachelor’s, Master’s, or equivalent practical experience in Computer Science, Data Science, Statistics, Mathematics, Physics, or an analytically grounded quantitative field. Experience: 5+ years of software engineering experience focusing on performance advertising, programmatic bidding, or large-scale user-conversion optimization loops.• Attribution Domain Expertise: Demonstrated track record of evaluating and implementing multi-touch attribution (MTA), last-touch attribution (LTA), or incrementality testing frameworks in a production environment. Data Engineering & Scale: Hands-on experience engineering pipelines handling terabyte-to- petabyte scale data via distributed frameworks such as Apache Spark, Apache Flink, Kafka, and cloud data warehouses (e.g., Snowflake, BigQuery). Format Versatility: Strong technical familiarity with technical specs supporting Mobile App (IDFA/GAID loss mitigations), CTV (App Transport Security, IFA standards), and Desktop environments. Preferred Qualifications Deep understanding of the OpenRTB protocol, DSP/SSP mechanics, and supply-path optimization (SPO). Experience deploying production-grade Machine Learning frameworks for CTR/CVR prediction. Strong system-level performance benchmarking skills (profiling memory allocation, reducing I/O bottlenecks. Pubmatic (Nasdaq: PUBM) is an independent technology company maximizing customer value by delivering digital advertising’s supply chain of the future. By operating on an AI-first architecture designed to make intelligence fundamental—not additive—PubMatic enables premium publishers and programmatic buyers to optimize continuously, preserve transparency, and achieve superior measurable outcomes at a global scale. Proces…