AI-Powered Platform Data Engineer for Self-Service Analytics

Amazon; Hawthorne (CA); On-site; USD 132,000 - 179,000; Full time

Job summary

Amazon is seeking a Platform Builder, a Data Engineer focused on building scalable data platforms and datasets powering subscription lifecycle analytics and monitoring services. You will design and maintain data pipelines, AI-native self-service platforms, and governance to ensure data quality and discoverability across subscription and monitoring ecosystems.

You will collaborate with software engineers, scientists, data analysts, and business stakeholders to deliver reliable subscriber

Qualifications

• 3+ years of data engineering experience.
• Experience with SQL.
• Experience with data modeling, warehousing and ETL pipelines.
• Experience building/operating highly available, distributed data systems.
• Experience developing, deploying and managing AI products at scale.

Responsibilities

• Build and maintain efficient, scalable data pipelines and curated datasets for AI/ML consumption.
• Deliver data solutions as a trusted partner to business stakeholders and data science teams.
• Develop and operate data pipelines using AWS services and internal tools, optimizing efficiency.
• Contribute to self-service data platforms enabling access to subscription and monitoring data.
• Implement data governance including data classification, PII detection, and lineage tracking.
• Support working sessions to help stakeholders adopt data capabilities.

Skills

Data engineering

SQL

Data modeling

ETL pipelines

AI at scale

Distributed systems

Education

Master's degree in CS/Engineering

Tools

AWS Redshift

S3

AWS Glue

EMR

Kinesis

Lambda

IAM

BI tools (QuickSight, Tableau, Power BI)

Job description

Amazon is seeking a Platform Builder, a Data Engineer focused on building scalable data platforms and datasets powering subscription lifecycle analytics and monitoring services. You will design and maintain data pipelines, AI-native self-service platforms, and governance to ensure data quality and discoverability across subscription and monitoring ecosystems.

You will collaborate with software engineers, scientists, data analysts, and business stakeholders to deliver reliable subscriber