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Senior Performance Advertising Engineer

📅 Jun 25
Real-time Bidding AlgorithmsPredictive ModelingData Pipeline EngineeringMulti-touch Attribution
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📜 Description

  • Own and drive the optimization of buyer-side and performance marketing systems.
  • Develop, benchmark, and deploy real-time bidding algorithms and predictive models to maximize ROAS.
  • Design and implement scalable, low-latency data pipelines for conversion and multi-touch attribution datasets.
  • Advance performance capabilities across programmatic formats in an omnichannel environment.
  • Build mechanisms for mobile environments that comply with privacy frameworks.
  • Innovate identity framework integrations for high attribution fidelity post-third-party cookies.

🛠️ Requirements

  • 5+ years of software engineering experience in performance advertising or programmatic bidding.
  • Bachelor's degree in engineering or equivalent from a recognized institution.
  • Expertise in multi-touch attribution and incrementality testing frameworks.
  • Experience with data pipelines handling terabyte-to-petabyte scale data.
  • Strong familiarity with technical specs for Mobile App, CTV, and Desktop environments.
  • Deep understanding of OpenRTB protocol and supply-path optimization.

✨ Benefits

  • Paternity/maternity leave
  • Healthcare insurance
  • Broadband reimbursement
  • Healthy snacks and drinks in the office
  • Catered lunches
Full job description

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.

We'd Love for You to Have:

  • 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.
  • 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.

Qualification:

Should have a bachelor’s degree in engineering or an equivalent degree from a well-known institute/university.

Additional Information:

Return to Office: PubMatic employees throughout the globe have returned to our offices via a hybrid work schedule (3 days “in office” and 2 days “working remotely”) that is intended to maximize collaboration, innovation, and productivity among teams and across functions.

Benefits: Our benefits package includes the best of what leading organizations provide, such as paternity/maternity leave, healthcare insurance, broadband reimbursement. As well, when we’re back in the office, we all benefit from a kitchen loaded with healthy snacks and drinks and catered lunches and much more!.

Diversity and Inclusion: PubMatic is proud to be an equal opportunity employer; we don’t just value diversity, we promote and celebrate it. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status

About PubMatic

PubMatic is one of the world’s leading scaled digital advertising platforms, offering more transparent advertising solutions to publishers, media buyers, commerce companies and data owners, allowing them to harness the power and potential of the open internet to drive better business outcomes.

Founded in 2006 with the vision that data-driven decisioning would be the future of digital advertising, we enable content creators to run a more profitable advertising business, which in turn allows them to invest back into the multi-screen and multi-format content that consumers demand.

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