Data Engineer II, Canada Product & Tech

The CA Retail Analytics team powers data-driven decision-making for one of Amazons fastest-growing retail organizations. We support critical business functions across 3P Prime Marketing Finance Cross Border Product North America Language Experience Supply Chain Excellence Canada Customer and Seller Experience Delivery Speed and Experience and other emerging CA Stores initiatives. As CAs footprint expands were building the foundational data infrastructure to enable self-service analytics GenAI integration and proactive insights at scale.

Were seeking a Data Engineer who thrives on building scalable reliable data systems that unlock business value. You are expected to architect and build large-scale high-performance data integration and data models that power business-critical analytics across CA Stores. Youll design and implement robust data solutions that handle massive data volumes from our Data Warehouse and distributed software systems enabling reporting dashboards and strategic decision-making for stakeholders across the organization. This is a foundational role where youll transform CAs analytics from reactive fragmented solutions into a systematic scalable data architecture that serves as the backbone for current and future business needs.

Key job responsibilities
What Youll Do
Build Scalable Data Infrastructure
Design and implement robust ETL/ELT pipelines using AWS technologies (Redshift S3 Glue EMR Lambda) to consolidate and normalize data across CA program footprints
Lead technical strategy with CA Techs Software Development team on upcoming product launches
Architect dimensional data models and semantic layers that enable self-service analytics and GenAI tools
Develop automated data quality frameworks with monitoring alerting and anomaly detection to ensure data reliability

Drive Operational Excellence
Optimize cluster performance and reduce IMR costs through systematic node assessment query tuning and resource management
Eliminate technical debt by building centralized data models and eliminating duplicate pipelines and implementing lifecycle management
Establish data engineering best practices including version control code reviews testing frameworks and comprehensive documentation
Mentor team members on data engineering principles and foster a culture of engineering excellence

Enable Innovation & Self-Service
Build AI-ready datasets with well-curated metadata and NLP-friendly schemas to support GenAI initiatives and conversational analytics
Partner with BIEs Data Scientists and Product teams to deliver production-grade datasets that power strategic insights
Create repeatable extensible data products and frameworks that scale across multiple CA business domains

Above all you should be passionate about working with huge data sets and someone who loves to bring datasets together to answer business questions and drive change.


About the team
Why This Role Matters
Amazon Canada Stores is scaling quickly and current data solutions were not built for the level of cross-domain complexity we are now operating in. The impact will be visible in how quickly leaders can access consistent metrics how efficiently teams build on shared datasets and how sustainably we scale new initiatives.

What Success Looks Like
First 90 days: Audit current infrastructure identify quick wins for cost optimization and establish DE best practices
6 months: Implement monitoring frameworks extensible frameworks and deliver first consolidated data models
12 18 months: Enable self-service analytics capabilities reduce IMR costs by X% and lay groundwork for GenAI integration; deliver AI-ready semantic layers establish automated data quality systems and position CA as a leader in analytics innovation


- 3 years of data engineering experience
- 3 years of developing and operating large-scale data structures for business intelligence analytics using SQL experience
- 3 years of developing and operating large-scale data structures for business intelligence analytics using ETL/ELT processes experience
- 3 years of developing and operating large-scale data structures for business intelligence analytics using data modeling experience
- Experience with data modeling warehousing and building ETL pipelines
- Bachelors degree

- Experience with AWS technologies like Redshift S3 AWS Glue EMR Kinesis FireHose Lambda and IAM roles and permissions
- Experience with non-relational databases / data stores (object storage document or key-value stores graph databases column-family databases)
- Bachelors degree or above in Science Technology Engineering or Mathematics (STEM) or experience in defining and creating benchmarks for assessing GenAI model performance
- Ability to recognize opportunities where generative AI could enhance products workflows or customer experiences.

Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status disability or other legally protected status.

Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process including support for the interview or onboarding process please visit for more information. If the country/region youre applying in isnt listed please contact your Recruiting Partner.

The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience qualifications and location. Amazon also offers comprehensive benefits including health insurance (medical dental vision prescription Basic Life & AD&D insurance and option for Supplemental life plans EAP Mental Health Support Medical Advice Line Flexible Spending Accounts Adoption and Surrogacy Reimbursement coverage) 401(k) matching paid time off and parental leave. Learn more about our benefits at WA Seattle - 132100.00 - 178800.00 USD annually