About The Position

The Ads Measurement Team builds and operates systems that measure, validate, and report on the effectiveness of advertising campaigns across Moloco’s platform. As a Senior Software Engineer, you will design, build, and scale highly reliable, observable, and low-latency data pipelines that power attribution, reporting, and third-party measurement integrations. You’ll work at the intersection of backend infrastructure, real-time data processing, and measurement offering, partnering closely with Partner Engineering, Data Science, and Product teams to ensure signal accuracy, data integrity, and trust at massive scale. Your work will directly impact advertiser confidence, model performance, and Moloco’s ability to deliver measurable business outcomes.

Requirements

  • Bachelor’s or Master’s degree in Computer Science, or equivalent technical field.
  • 5+ years of backend-infrastructure software development industry experience.
  • Proficiency in one or more backend languages: Go (preferred), Python or Java.
  • Experience building data pipelines and optimizing real-time or near real-time stream processing systems with low latency and high throughput.
  • Strong understanding of real-time, multi-threaded, parallel processing and distributed systems.
  • Operate and scale containerized services and data platforms using tools like Kubernetes, Airflow, and BigQuery.

Nice To Haves

  • Experience in ad tech or with measurement systems, including MMPs, SKAN, and attribution platforms.
  • Experience integrating with third-party APIs at scale.
  • Experience implementing comprehensive monitoring and observability using modern monitoring tools (e.g., Datadog, Prometheus).
  • Experience designing and maintaining resilient data pipelines optimized for large-scale event data.

Responsibilities

  • Develop high-throughput, low-latency real-time and batch data processing systems, optimizing performance at scale.
  • Implement, maintain, and support third-party measurement and attribution integrations, including MMPs.
  • Design, build, and operate reliable, observable measurement pipelines that ensure data accuracy and completeness.
  • Optimize and scale production data infrastructure using Kubernetes, Airflow, and BigQuery, applying infrastructure-as-code, CI/CD, and cost-efficient reliability best practices.
  • Collaborate closely with Machine Learning, Data Science, and Engineering teams to deliver high-quality measurement signals, support model training, and mentor engineers across the organization.
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