Amazon Data Engineer III Amazon Key 

United States, Washington, Seattle 

226700209

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 software engineers, product managers, and analytics teams 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 (e.g., GDPR, SOC2).
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.

- Bachelor’s degree in Computer Science, Engineering, or a related technical discipline
- 7+ years of relevant work experience in data engineering, business intelligence or related field
- Advanced proficiency in SQL, ETL management, data modeling, warehousing and building ETL pipelines
- Experience in at least one modern scripting or programming language, such as Python, Java, Scala, or NodeJS
- Strong critical thinking skills and attention to detail
- Experience mentoring team members on best practices

- Advanced degree (Master's) in Computer Science, Computer Engineering, or a quantitative field preferred
- Experience in leading and architecting Data solutions using AWS data services (Redshift, S3, Glue, EMR, Kinesis, Lambda, RDS, Bedrock) and understanding of IAM security frameworks.
- Proven track record of tackling highly ambiguous, complex data challenges and delivering impactful solutions.
- Hands-on experience working with large language models, including understanding of data infrastructure requirements for AI model training.