We are seeking an experienced Principal Engineer to lead the evolution and optimization of high-scale programmatic reporting systems at Amazon Ads. This role will drive the technical vision for how advertisers and partners receive campaign measurement data - billions of data points daily, delivered through streaming, batch, and on-demand interfaces to thousands of integrators worldwide.
Amazon Ads customers - from emerging brands to global enterprises - depend on accurate measurement to understand what's working, optimize their strategies, and make informed investment decisions. Our programmatic reporting infrastructure delivers this data at massive scale, powering AI agents, machine learning models, analytics engines, and dashboards across the advertising ecosystem. The systems you architect will directly determine how efficiently and elegantly we put data into the hands of the world's most sophisticated advertising customers.
This is a role defined by hard problems with measurable impact. The infrastructure that powers our data delivery capabilities processes billions of data points daily across streaming, batch, and real-time surfaces. As AI agents increasingly consume our data programmatically, we need fundamentally new approaches to how we partition, cache, and serve reporting data at scale. You will pioneer architectures that are not just fast and reliable, but elegantly efficient - systems where performance and cost-effectiveness emerge naturally from sound design rather than brute-force scaling.
As part of the Programmatic Reporting team, you will define the multi-year technical vision and execution strategy for our data delivery systems. You will architect solutions spanning streaming pipelines, batch report generation, and emerging real-time interfaces. You will collaborate across organizations - working with measurement teams, cloud infrastructure teams, and partner-facing teams to build systems that are efficient, consistent, and elegant. You will be hands-on: reading code, running benchmarks, prototyping solutions, and making architecture decisions grounded in data.
The ideal candidate will have deep expertise in distributed systems optimization, streaming architectures at scale, and a proven track record of putting data directly into the hands of sophisticated customers through high-performance programmatic interfaces. They will be equally comfortable writing a technical deep-dive document for VP-level leadership as they are profiling query execution plans or benchmarking data formats. They will bring clarity to ambiguous problems, build consensus across teams with competing priorities, and deliver solutions that are simple, maintainable, and measurably impactful.
Key job responsibilities
System Architecture and Efficiency: Lead the design of data delivery infrastructure that is performant, reliable, and elegantly cost-efficient. Architect solutions where efficiency emerges from sound design - sharding strategies, partitioning models, and execution plans that naturally balance latency, throughput, and resource utilization.
Streaming Architecture Evolution: Drive the evolution of our streaming data delivery systems toward truly stream-native architectures. Solve dimensional mutation and data restatement challenges in streaming contexts. Pioneer approaches that serve customers with fresher data at lower operational overhead.
Data Delivery Innovation: Design new approaches to deliver large datasets to customers efficiently. Establish clear ownership boundaries between data systems that encourage accountability. Build unified transformation libraries enabling consistency across all reporting surfaces.
Technical Vision and Strategy: Define and drive the 3-year technical roadmap for programmatic reporting systems. Write strategic narratives and present technical decisions to senior leadership. Provide input into annual planning processes and investment prioritization.
Cross-Organizational Leadership: Build consensus across multiple engineering organizations with different priorities. Lead architectural reviews and provide critical, constructive feedback. Mentor senior engineers on the path to Principal level. Foster a culture of engineering excellence through code, designs, and technical standards.
Emerging Capabilities: Architect systems for AI-native data access patterns - cardinality estimation, predictive query routing, and agent-optimized delivery. Design for the next generation of programmatic data consumers.
About the team
The Measurement and Data Science (MADS) organization sits at the heart of Amazon Ads, responsible for data infrastructure, measurement, research, and reporting that enables advertisers to understand and optimize their advertising investments.
Within MADS, the Programmatic Reporting team builds the data systems that power how advertisers and partners measure their Amazon Ads outcomes. We own Amazon Marketing Stream and the Reporting APIs, delivering accurate, consistent, and timely data at massive scale. Our work spans distributed systems engineering, streaming architecture, batch optimization, and data delivery - with emerging opportunities in AI-native interfaces. We move fast, think in systems, obsess over efficiency, and measure everything.
BASIC QUALIFICATIONS
- 10+ years of professional software development experience
- 7+ years of designing and building large-scale distributed systems
- Experience leading technical strategy and architecture for organizations of 30+ engineers
- Deep expertise in at least two of: stream processing (Kafka, Flink, Kinesis), batch processing (Spark, EMR), or columnar data systems (Parquet, Iceberg, Delta Lake)
- Proven track record of delivering high-performance data systems that put data directly into the hands of sophisticated customers through programmatic interfaces
- Experience presenting technical strategies to senior executive leadership
- Bachelor's degree in Computer Science or equivalent
PREFERRED QUALIFICATIONS
- Experience with advertising technology platforms or large-scale reporting systems
- Expertise in query optimization, execution planning, and OLAP systems
- Experience with AWS cloud infrastructure (S3, EMR, SQS, Kinesis, Firehose)
- Publications, talks, or recognized thought leadership in distributed systems or data infrastructure
- Experience mentoring engineers to Staff/Principal level
- Track record of building consensus across organizations with competing technical priorities
The base salary range for this position is listed below. As a total compensation company, Amazon's package may include other elements such as sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon offers comprehensive benefits including health insurance (medical, dental, vision, prescription, basic life & AD&D insurance), Registered Retirement Savings Plan (RRSP), Deferred Profit Sharing Plan (DPSP), paid time off, and other resources to improve health and well-being. We thank all applicants for their interest, however only those interviewed will be advised as to hiring status.
CAN, ON, Toronto - 185,400.00 - 309,600.00 CAD annually
