Data Engineer, Deal Tooling and Insights, Strategic Customer Engagements

Description

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? 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?

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? 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?

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.

• 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, Sage Maker, 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)

• Bachelor's degree or foreign equivalent in Computer Science, Engineering, Information Systems, Mathematics, or a related field
• 3+ years of data engineering experience
• 1+ years of developing and operating large-scale data structures for business intelligence analytics using each of the following: ETL (Extract, Transform, Load)/ELT (Extract, Load, Transform) processes experience
• 1+ years of developing and operating large-scale data structures for business intelligence analytics using SQL experience
• 1+ 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

• Experience with AWS technologies like Redshift, S3, AWS Glue, EMR, Kinesis, Fire Hose, 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.

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