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Sr. Software Development Engineer, Advanced Analytics

Amazon

Sr. Software Development Engineer, Advanced Analytics

full-timePosted: Apr 1, 2026Updated: Aug 27, 2026Seattle, Washington, United States

Job Description

We build advanced analytic solutions to support the measurement and intelligence needs of Amazon's most strategic advertising customers — Holding Companies, independent agencies, technology integrators, and large-scale advertisers. We own and operate the premier advanced analytics capability within Amazon Ads, delivering cutting-edge AI, modeling, and data solutions that empower our customers to make smarter, faster, and more impactful advertising decisions. In the programmatic advertising industry, transparency has become increasingly critical as the ecosystem expands with multiple layers in the ad selling and buying supply chain. Log-level data—granular, non-aggregated, event-level information from ad servers, exchanges, and SSPs—provides advertisers with unprecedented visibility into individual ad impressions, bid prices, viewability scores, and supply path. This role will build the foundational infrastructure to capture, process, store, and analyze this raw data at petabyte scale, empowering our organization to understand auction competitiveness, identify revenue opportunities, optimize floor pricing, and ensure supply chain transparency. As a Senior Software Development Engineer on the Log-Level Data team, you will build the foundational infrastructure to capture, process, store, and analyze this raw data at petabyte scale. Your work will empower our organization to understand auction competitiveness, identify revenue opportunities, optimize floor pricing, and ensure supply chain transparency for Amazon's largest advertising partners. The ideal candidate is a creative, demonstrated leader with excellent analytical abilities and a strong drive to deliver results. You should be passionate about solving complex technical challenges, comfortable operating in ambiguous environments, and excited about the opportunity to build foundational infrastructure that will power the next generation of advertising measurement and transparency solutions. This role requires deep technical expertise, strong problem-solving skills, and exceptional communication abilities. You should be able to think strategically about system architecture while also diving deep into implementation details. You'll need to balance competing priorities, make pragmatic trade-offs, and maintain high standards for code quality and operational excellence. Key job responsibilities - Design and build highly scalable, fault-tolerant data pipelines to ingest, process, and store petabyte-scale log-level advertising data from multiple sources including ad servers, exchanges, and SSPs - Architect distributed systems that enable real-time and batch processing of granular event-level data with sub-second latency requirements - Develop robust data quality frameworks to validate, cleanse, and enrich raw log data while maintaining data lineage and audit trails - Create efficient storage solutions optimized for both high-throughput writes and complex analytical queries across massive datasets - Build APIs and data access layers that enable downstream analytics, modeling, and reporting applications to leverage log-level data - Collaborate with data scientists, product managers, and business stakeholders to translate transparency and measurement requirements into technical solutions - Establish operational excellence practices including monitoring, alerting, and automated recovery mechanisms for mission-critical data infrastructure - Mentor junior engineers and contribute to the technical direction of the team through design reviews, code reviews, and architectural discussions - Drive innovation in data processing techniques, exploring emerging technologies and methodologies to improve system performance and capabilities

Locations

  • Seattle, Washington, United States

Salary

168,100 - 227,400 USD / yearly

Skills Required

  • natural language processingintermediate

Required Qualifications

  • 5+ years of non-internship professional software development experience (experience, 5 years)
  • 5+ years of programming with at least one software programming language experience (experience, 5 years)
  • 5+ years of leading design or architecture (design patterns, reliability and scaling) of new and existing systems experience (experience, 5 years)
  • Experience as a mentor, tech lead or leading an engineering team (experience)

Preferred Qualifications

  • 5+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience (experience, 5 years)
  • Bachelor's degree in computer science or equivalent (degree in computer science or equivalent)
  • Experience with natural language processing and generative model architectures (experience)
  • Demonstrated track record of innovative AI solution development (experience)

Responsibilities

  • Design and build highly scalable, fault-tolerant data pipelines to ingest, process, and store petabyte-scale log-level advertising data from multiple sources including ad servers, exchanges, and SSPs
  • Architect distributed systems that enable real-time and batch processing of granular event-level data with sub-second latency requirements
  • Develop robust data quality frameworks to validate, cleanse, and enrich raw log data while maintaining data lineage and audit trails
  • Create efficient storage solutions optimized for both high-throughput writes and complex analytical queries across massive datasets
  • Build APIs and data access layers that enable downstream analytics, modeling, and reporting applications to leverage log-level data
  • Collaborate with data scientists, product managers, and business stakeholders to translate transparency and measurement requirements into technical solutions
  • Establish operational excellence practices including monitoring, alerting, and automated recovery mechanisms for mission-critical data infrastructure
  • Mentor junior engineers and contribute to the technical direction of the team through design reviews, code reviews, and architectural discussions
  • Drive innovation in data processing techniques, exploring emerging technologies and methodologies to improve system performance and capabilities

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