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