Data Engineer: Scalable Pipelines & AI-Driven Data

Amazon; New York (NY); On-site; USD 145,000 - 197,000; Full time

Job summary

Amazon seeks a Data Engineer for Deal Tooling and Insights within Strategic Customer Engagements in New York. Design and manage scalable data pipelines and data products powering analytics, machine learning, and AI-enabled systems.

Collaborate with BI engineers and product teams, implement data structures and semantic layers, and deploy infrastructure-as-code using CDK. Ensure data quality, monitoring, and reliable data delivery across the data platform.

Qualifications

• Bachelor's degree or foreign equivalent in CS, Eng, IS, Math, or related field.
• 3+ years of data engineering experience.
• 1+ years of ETL/ELT experience for BI analytics.
• 1+ years of SQL experience for BI analytics.
• 1+ years of data modeling for BI analytics.
• Experience with data modeling, warehousing and ETL pipelines.

Responsibilities

• Architect scalable, reliable data pipelines from diverse sources.
• Manage AWS resources: Redshift, S3, Glue, EMR, Kinesis, Firehose, Lambda, IAM.
• Deploy infrastructure-as-code using CDK.
• Oversee production operations: optimize data delivery, scale infrastructure, deployments.
• Design data structures and data models to support reporting and ML.
• Build semantic layers and knowledge graphs for intelligent data access.
• Develop infrastructure for AI systems with multi-agent orchestration.
• Ensure data quality via monitoring, validation, auditing, documentation of pipelines.

Skills

Data engineering

SQL

Data modeling

ETL/ELT pipelines

Warehousing

Education

Bachelor's degree or foreign equivalent in Computer Science, Engineering, Information Systems, Mathematics, or related field

Tools

Redshift

S3

AWS Glue

EMR

Kinesis

Firehose

Lambda

IAM

Job description

Amazon seeks a Data Engineer for Deal Tooling and Insights within Strategic Customer Engagements in New York. Design and manage scalable data pipelines and data products powering analytics, machine learning, and AI-enabled systems.

Collaborate with BI engineers and product teams, implement data structures and semantic layers, and deploy infrastructure-as-code using CDK. Ensure data quality, monitoring, and reliable data delivery across the data platform.