Senior Performance Advertising Engineer
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. You will partner closely with data scientists and product teams to translate business objectives into scalable technical solutions that directly impact revenue and efficiency. The role demands a high degree of ownership, analytical rigor, and the ability to operate in a fast-paced, ambiguity-driven environment. You will be a key architect in maintaining our competitive edge in performance advertising technology.
Key facts
What you'll do
Design, 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).
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.
Advance PubMatic's performance capabilities across specific programmatic formats by defining and executing technical strategies for incremental gains.
Build robust mechanisms that thrive within SKAdNetwork, Attribution API, and Android Privacy Sandbox constraints to ensure continuity and accuracy in mobile measurement.
Implement precise cross-device graph integrations, household-level frequency capping, and server-to-server attribution systems for CTV and Video environments.
Innovate alternative identity framework integrations (e.g., UID2, LiveRamp ATS) to sustain high attribution fidelity post-third-party cookies in Desktop environments.
Constantly audit existing data ingestion points for architectural flaws, data loss, or systemic latencies that negatively skew attribution accuracy and campaign performance.
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.
Collaborate with cross-functional stakeholders to define success metrics, troubleshoot production issues, and prioritize roadmap items based on technical feasibility and business impact.
Lead technical design reviews and code quality standards to ensure maintainability, scalability, and security of performance-critical systems.
Conduct performance benchmarking and root cause analysis for latency, throughput, and accuracy issues across the entire data pipeline.
Champion best practices in data engineering, machine learning operations, and distributed systems to streamline workflows and reduce technical debt.
Translate complex business requirements into technical specifications and communicate progress effectively to both technical and non-technical audiences.
Mentor junior engineers by providing guidance on system design, coding standards, and debugging techniques within the performance advertising domain.
Requirements
Must have a bachelor's degree in engineering or an equivalent degree from a recognized institute.
Possess a minimum of 5 years of software engineering experience focusing on performance advertising, programmatic bidding, or large-scale user-conversion optimization loops.
Demonstrate a proven track record of evaluating and implementing multi-touch attribution (MTA), last-touch attribution (LTA), or incrementality testing frameworks in a production environment.
Have 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).
Show strong technical familiarity with technical specs supporting Mobile App (IDFA/GAID loss mitigations), CTV (App Transport Security, IFA standards), and Desktop environments.
Possess deep understanding of the OpenRTB protocol, DSP/SSP mechanics, and supply-path optimization (SPO).
Have experience deploying production-grade Machine Learning frameworks for CTR/CVR prediction.
Exhibit strong system-level performance benchmarking skills, including profiling memory allocation and reducing I/O bottlenecks.
Practical notes
The role is based in Gurugram, India, and operates on a full-time basis. There are no specific travel requirements, visa sponsorships, or application deadlines mentioned in the current source documentation. Candidates should ensure they meet the educational and experience prerequisites outlined in the qualification section before applying.