Data Engineer, Deal Tooling and Insights, Strategic Customer Engagements

Do you love building scalable data pipelines and engineering reliable datasets? Are you excited by the opportunity to create foundational data infrastructure that powers decision-making across AWS? Do you want to work in a fast-paced environment, solving data challenges at the intersection of engineering and business impact?

If so, we are looking for a Data Engineer to join the Strategic Customer Engagements team to develop a scalable data analytics platform. The Strategic Customer Engagements Deal Team works with our customers on commercial private pricing opportunities to meet their desired business outcomes while ensuring alignment with AWS business objectives.

In this role, you will design and manage large-scale data systems using cloud-native approaches to scalability and automation. You will build robust pipelines, integrate new data sources, and deliver reliable data products that support analytics, machine learning, and AI-powered systems. Working closely with business intelligence engineers and product teams, you will work backwards from business questions to build solutions that meet customer needs. The role will leverage generative AI and AWS services to raise the bar on how the team consumes and acts on data, and to build the next generation of AI-enabled data platforms.

Key job responsibilities
Key Job Responsibilities

- Architect and implement scalable, reliable, and secure data pipelines for extraction, transformation, and loading from diverse data sources
- Manage AWS resources including EC2, Redshift, Glue, S3, SageMaker, App Studio, and Bedrock
- Deploy infrastructure-as-code using CDK
- Oversee production operations, including optimizing data delivery, scaling infrastructure, code deployments, bug fixes, and release management
- Design and implement data structures using best practices in data modeling to support reporting, analysis, and machine learning
- Build semantic layers and knowledge graphs enabling intelligent query routing and context-aware data access
- Develop infrastructure for agentic AI systems with multi-agent orchestration
- Ensure data quality through monitoring, validation, auditing, and documentation of pipelines and data sources
- Read, write, and debug data processing and orchestration code following best coding standards (e.g., version controlled, code reviewed)