Software Engineer, Commercial Intelligence and Analytics

Responsibilities

• Own and maintain production systems that surface revenue performance, portfolio health, and client opportunity.
• Design and operate proactive insight pipelines, translating business needs into system architecture and data models.
• Build and deploy automated tools and signals to help Sales and Client Services teams prioritize effort and identify risk.
• Integrate AI and LLM capabilities into workflows to automate documentation and improve pipeline quality.
• Develop production-grade data assets and pipelines using SQL and Python to ensure reliability and maintainability.
• Translate ambiguous commercial problems into concrete technical plans and stakeholder-aligned requirements.

Requirements

• 5+ years of experience in analytics engineering, data engineering, software engineering, or a similar systems-oriented role.
• Strong SQL skills with experience working with large, complex datasets in modern data environments.
• Proficiency in Python for building production systems, automation, and data pipeline development.
• Strong foundation in software development practices, including Git, code review, testing, and CI/CD pipelines.
• Proven ability to translate business requirements into technical designs and system architecture.
• Experience building durable, automated systems rather than relying on manual or ad hoc processes.

Preferred Qualifications

• Experience supporting Sales, Client Services, or Revenue Operations teams in analytically rigorous environments.
• Experience building and maintaining production ETL/ELT systems or data pipelines.
• Familiarity with advertising technology, digital media, or platform-based commercial models.
• Experience with enterprise data platforms such as Snowflake or Databricks.

About the Company

The Trade Desk is a global technology company and the world’s leading independent platform for digital advertising. Our technology helps advertisers reach the right audiences across the open internet—from streaming TV and podcasts to mobile apps and news. We solve unique technical challenges, from processing massive datasets in real time to building systems that operate reliably on a global scale.