Senior Data Engineer - AI-Driven Data Infrastructure

Amazon Web Services (AWS); Seattle (WA); On-site; USD 155,000 - 209,000; Full time

Benefits offered by this job

Health insurance

401(k) matching

Paid time off

Parental leave

Job summary

Amazon Development Center U.S., Inc. in Seattle is seeking a Senior Data Engineer to design and maintain a next-generation data infrastructure that serves both human analysts and AI systems.

You will bridge traditional data warehousing with AI technologies, ensuring data accuracy, lineage, and observability at scale, while collaborating across data scientists, engineers, and business stakeholders.

Qualifications

• 7+ years of data engineering experience.
• Experience building data infrastructure for AI systems and autonomous agents.
• Experience with GenAI data patterns end to end: chunking, embeddings, vector stores.
• Experience maintaining datasets and feature pipelines for ML/GenAI training and inference.
• Experience with data quality, lineage, and observability at scale.
• Strong Python (or Scala/Java) and advanced SQL skills.

Responsibilities

• Design and operate production data pipelines and warehouses.
• Build data infrastructure that serves AI systems and autonomous agents.
• Develop end-to-end GenAI data patterns: chunking, embeddings, vector stores.
• Create datasets/feature pipelines for ML/GenAI training and inference.
• Implement data quality, lineage, and observability for AI workloads.
• Collaborate with data scientists, engineers, and stakeholders.

Skills

Python

SQL

Data engineering

Mentoring

ETL/ELT

GenAI data patterns

Batch/Streaming ETL

Cloud data pipelines

Education

Bachelor's degree in CS/Engineering/Analytics/Math/Statistics/IT

Tools

Amazon Redshift

Glue

EMR/Spark

SageMaker

Bedrock

Airflow

Step Functions

Glue Workflows

S3

Job description

Amazon Development Center U.S., Inc. in Seattle is seeking a Senior Data Engineer to design and maintain a next-generation data infrastructure that serves both human analysts and AI systems.

You will bridge traditional data warehousing with AI technologies, ensuring data accuracy, lineage, and observability at scale, while collaborating across data scientists, engineers, and business stakeholders.