Sr. Software Development Engineer, Advanced Analytics
We build advanced analytic solutions that power measurement and intelligence for Amazon Ads' most strategic customers: Holding Companies, independent agencies, technology integrators, and large-scale advertisers. Our team owns and operates the premier advanced analytics capability within Amazon Ads, delivering innovative AI, modeling, and data solutions that help customers make smarter, faster, and more impactful advertising decisions.
Transparency is reshaping programmatic advertising. As the ecosystem grows (with multiple layers in the ad buying and selling supply chain) advertisers demand granular visibility into every impression, bid, viewability score, and supply path. Log-level data makes this possible: raw, non-aggregated, event-level signals from ad servers, exchanges, and SSPs that unlock insights no dashboard summary can provide.
As a Senior Software Development Engineer on the Log-Level Data team, you will design and build the foundational infrastructure to ingest, process, store, and analyze this data at petabyte scale. Your systems will power our organization's ability to understand auction dynamics, surface revenue opportunities, optimize floor pricing, and deliver supply-chain transparency to Amazon's largest advertising partners. You'll own end-to-end, from architecture and implementation through to production operations, and your work will directly shape the next generation of advertising measurement.
What we're looking for:
You are a creative, proven technical leader who thrives on ambiguity and loves building from zero-to-one. You bring deep expertise in distributed systems and large-scale data processing, strong analytical instincts, and the drive to ship high-quality solutions at pace. You think strategically about system architecture and dive deep into implementation details. You balance competing priorities with pragmatic trade-offs, communicate clearly across technical and business audiences, and hold yourself and your team to a high bar for code quality and operational excellence.
If you're excited by the chance to build foundational infrastructure that powers transparency across one of the world's largest advertising platforms, we'd love to talk.
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
Transparency is reshaping programmatic advertising. As the ecosystem grows (with multiple layers in the ad buying and selling supply chain) advertisers demand granular visibility into every impression, bid, viewability score, and supply path. Log-level data makes this possible: raw, non-aggregated, event-level signals from ad servers, exchanges, and SSPs that unlock insights no dashboard summary can provide.
As a Senior Software Development Engineer on the Log-Level Data team, you will design and build the foundational infrastructure to ingest, process, store, and analyze this data at petabyte scale. Your systems will power our organization's ability to understand auction dynamics, surface revenue opportunities, optimize floor pricing, and deliver supply-chain transparency to Amazon's largest advertising partners. You'll own end-to-end, from architecture and implementation through to production operations, and your work will directly shape the next generation of advertising measurement.
What we're looking for:
You are a creative, proven technical leader who thrives on ambiguity and loves building from zero-to-one. You bring deep expertise in distributed systems and large-scale data processing, strong analytical instincts, and the drive to ship high-quality solutions at pace. You think strategically about system architecture and dive deep into implementation details. You balance competing priorities with pragmatic trade-offs, communicate clearly across technical and business audiences, and hold yourself and your team to a high bar for code quality and operational excellence.
If you're excited by the chance to build foundational infrastructure that powers transparency across one of the world's largest advertising platforms, we'd love to talk.
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