Data Engineer, Applied AI Solutions
4 days ago
We are seeking a Data Engineer to design, build and maintain our next-generation data infrastructure - one that seamlessly serves both human analysts and AI systems. This role sits at the intersection of traditional enterprise data warehousing and innovative AI technologies, requiring someone who can bridge these worlds to create a unified, future-proof data ecosystem.
As a key member of our data team, you'll collaborate across organizational boundaries with data scientists, engineers, analytics teams, and business stakeholders to develop innovative and scalable solutions that push the boundaries of what's possible with our data assets.
You'll be responsible for ensuring our datasets maintain the highest levels of accuracy, consistency, and observability - implementing comprehensive monitoring, lineage tracking, and self-healing mechanisms that maintain data quality at scale. Your infrastructure will support both analysts / scientists and autonomous AI agents with equal effectiveness, requiring thoughtful interfaces, documentation, and metadata that serve both audiences.
In this role, you'll champion a forward-thinking approach to data infrastructure that anticipates the evolving needs of AI systems while maintaining the reliability and performance that business operations demand. You'll help shape our technical roadmap for data systems that will serve as the foundation for our organization's AI transformation journey.
Key job responsibilities
Architect and implement scalable data infrastructure that enables both traditional analytics and modern AI/ML workflows
Design data models and pipelines that optimize for AI readiness while maintaining traditional reporting capabilities
Build robust ETL/ELT processes to ingest, transform, and prepare data for varied consumption patterns
Develop APIs and interfaces that allow AI agents to programmatically discover, access, and utilize enterprise data
Implement vector databases and embedding storage solutions for AI applications
Create data quality frameworks that ensure both human and AI consumers can trust the data
Establish metadata management systems that make data discoverable and understandable
Collaborate with data science and AI teams to understand their infrastructure requirements
Basic Qualifications:
- 3+ years of data engineering experience
- Experience with data modeling, warehousing and building ETL pipelines
Preferred Qualifications:
- 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)
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 you're applying in isn't listed, please contact your Recruiting Partner.
Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $118,900/year in our lowest geographic market up to $205,600/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, please visit This position will remain posted until filled. Applicants should apply via our internal or external career site.
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