AdTechTalent
Programmatic4 days agoHybrid

PubMatic

Senior Performance Advertising Engineer

performance advertisingprogrammaticreal-time biddingRTBROASattributionmulti-touch attributionMTAdata pipelinesstreaming databatch datamobile appCTVconnected TVvideodesktopSKAdNetworkPrivacy SandboxOpenRTBDSPSSPmachine learningCTR predictionCVR predictionApache SparkApache FlinkKafkaSnowflakeBigQueryPythonGoJavaC++

Key details

Salary

Not specified

Employment type

Full-time

Seniority

Senior

Years experience

5-10

Location

New York, US; Redwood City, United States

Full job description

Seeking a Senior Performance Advertising Engineer to optimize buyer-side and performance marketing systems. Responsibilities include designing algorithms, building data systems, and refining optimization loops to maximize ROAS for Advertisers and Agencies. Role involves ownership of technical architecture and scaling data pipelines for attribution data across Mobile App (including SKAdNetwork and Privacy Sandbox), Video, Connected TV, and Desktop. Develop and deploy real-time bidding algorithms, pacing controls, and predictive models. Design scalable streaming and batch data pipelines for multi-touch attribution datasets. Improve performance capabilities across programmatic formats including Mobile, CTV & Video, and Desktop. Audit data ingestion for flaws affecting attribution accuracy. Write high-performance, low-latency code in Python, Go, Java, or C++. Requires 5+ years software engineering experience in performance advertising or programmatic bidding, expertise in multi-touch attribution, and experience with large-scale data pipelines using Apache Spark, Flink, Kafka, and cloud warehouses like Snowflake or BigQuery. Preferred qualifications include knowledge of OpenRTB, DSP/SSP mechanics, supply-path optimization, and deploying machine learning for CTR/CVR prediction. Benefits include paid leave, holidays, healthcare, dental, vision, disability, life insurance, commuter benefits, wellness programs, unlimited DTO, mobile reimbursement, stocked pantries, and catered lunches. Location is hybrid with options for remote work from Redwood City or New York City.

What you'll do

  • Develop, benchmark, and deploy real-time bidding (RTB) algorithms, pacing controls, and predictive models to maximize ROAS and conversion tracking across all screens (CTV, Mobile App, Video, Desktop)
  • Design, evaluate, and implement scalable, low-latency streaming and batch data pipelines for complex conversion and multi-touch attribution (MTA) datasets
  • Advance performance capabilities across programmatic formats: Mobile (SKAdNetwork, Attribution API, Android Privacy Sandbox), CTV & Video (cross-device graph integrations, household-level frequency capping, server-to-server attribution), Desktop (alternative identity framework integrations like UID2, LiveRamp ATS)
  • Audit existing data ingestion points for architectural flaws, data loss, or systemic latencies affecting attribution accuracy and campaign performance
  • Write high-performance, low-latency, memory-efficient code in Python, Go, Java, or C++ for ultra-scaled backend processing trillions of monthly events

Requirements

  • Bachelor’s, Master’s, or equivalent practical experience in Computer Science, Data Science, Statistics, Mathematics, Physics, or an analytically grounded quantitative field
  • 5+ years of software engineering experience focusing on performance advertising, programmatic bidding, or large-scale user-conversion optimization loops
  • Demonstrated track record of evaluating and implementing multi-touch attribution (MTA), last-touch attribution (LTA), or incrementality testing frameworks in a production environment
  • 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)
  • Strong technical familiarity with technical specs supporting Mobile App (IDFA/GAID loss mitigations), CTV (App Transport Security, IFA standards), and Desktop environments
  • Preferred: Deep understanding of the OpenRTB protocol, DSP/SSP mechanics, and supply-path optimization (SPO)
  • Preferred: Experience deploying production-grade Machine Learning frameworks for CTR/CVR prediction
  • Preferred: Strong system-level performance benchmarking skills (profiling memory allocation, reducing I/O bottlenecks)

Tech stack

PythonGoJavaC++Apache SparkApache FlinkKafkaSnowflakeBigQuerySKAdNetworkPrivacy SandboxOpenRTBDSPSSPUID2LiveRamp ATSMachine Learning

Benefits

Paid leave programsPaid holidaysHealthcare insuranceDental insuranceVision insuranceDisability insuranceLife insuranceCommuter benefitsPhysical and financial wellness programsUnlimited discretionary time off (DTO) in the USReimbursement for mobileFully stocked pantriesIn-office catered lunches 5 days a week

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