Amazon Senior Data Engineer Mechatronics Sustainable Packaging 

United States, Washington, Bellevue 

635258707

In this role, you will work on unifying fragmented data pipelines, building robust data models, and ensuring reliable data lineage across multiple product areas. You will partner closely with business intelligence engineers, software engineers and product managers to develop data solutions that drive innovation and operational excellence.
Key job responsibilitiesDesign and enforce data modeling standards, data lineage, and governance frameworks that ensure consistency, reusability, and quality across systems.
Lead design and code reviews, driving engineering best practices across data development, documentation, testing, and monitoring.
Build data platforms and frameworks that support both batch and real-time processing, enabling flexible, efficient analytics at scale.
Implement secure and compliant data solutions that meet internal and external regulatory requirements
Evaluate and introduce emerging technologies to improve data platform performance, cost efficiency, and scalability.
Collaborate with cross-functional teams to gather data requirements, define solution architectures, and ensure alignment with business needs.

- 7+ years of data engineering, database engineering, business intelligence or business analytics experience
- Experience with data modeling, warehousing and building ETL pipelines
- Experience building/operating highly available, distributed systems of data extraction, ingestion, and processing of large data sets
- Experience building data products incrementally and integrating and managing data sets from multiple sources
- Experience communicating with users, other technical teams, and management to collect requirements, describe data modeling decisions and data engineering strategy
- Knowledge of data mining techniques, predictive analytics, and statistical modeling

- Master's degree
- Knowledge of professional software engineering & best practices for full software development life cycle, including coding standards, software architectures, code reviews, source control management, continuous deployments, testing, and operational excellence