Data Engineer II, IAM and Abuse Prevention

About the role

The ISAP SafeGuard team mixes long-term, high-impact projects with near-term innovative solutions to prevent abuse across Amazon. We balance Bias for Action, Dive Deep, Invent and Simplify, and Customer Trust daily. Our team embraces new approaches, technology, and innovation while ensuring our solutions are scalable, accurate, and drive action. We work with some of the most sensitive data at Amazon, which requires thoughtful engineering, strict access controls, and a strong sense of responsibility.

Responsibilities

• Design, implement, and maintain scalable ETL/ELT pipelines that ingest and transform security telemetry, authorization logs, compliance data, and operational metrics from diverse sources across Amazon
• Create and optimize data models that enable security engineers and scientists to efficiently query and analyze abuse patterns across billions of events
• Build ML-ready datasets for data science and applied science teams
• Own monitoring, alerting, and observability for all data pipelines and data solutions, proactively identifying and resolving data quality issues
• Review and modernize existing data infrastructure, proposing architectural improvements that increase reliability, reduce cost, and improve performance
• Design and build new data capabilities from the ground up to support product launches and investigation team needs
• Partner with security engineers, scientists, and investigators to understand their data requirements and build solutions that accelerate abuse detection and response
• Collaborate with data scientists and applied scientists to support AI and AI-agent-centric solutions, ensuring proper data engineering underpins model training and inference
• Leverage GenAI and ML tools to enhance your own workflows, automate pipeline operations, and improve data quality processes
• Develop deep understanding of partner teams and their capabilities, identifying opportunities to consume new signals and vend intelligence data to downstream consumers

Requirements

• 3+ years of data engineering experience
• 1+ years of developing and operating large-scale data structures for business intelligence analytics using ETL/ELT processes
• 1+ years of developing and operating large-scale data structures for business intelligence analytics using OLAP technologies
• 1+ years of developing and operating large-scale data structures for business intelligence analytics using data modeling
• 1+ years of developing and operating large-scale data structures for business intelligence analytics using SQL
• Experience with data modeling, warehousing and building ETL pipelines
• Experience with AWS technologies like Redshift, S3, AWS Glue, EMR, Kinesis, FireHose, Lambda, and IAM roles and permissions

Preferred Qualifications

• Experience with non-relational databases / data stores (object storage, document or key-value stores, graph databases, column-family databases)
• Experience in building analytic or scientific data products or solutions
• Experience managing confidential and sensitive employee information and adherence to strict confidentiality standards
• Experience with large scale distributed systems such as Hadoop, Spark etc.
• Experience using managed ML/AI solutions
• Experience with GenAI tools and techniques for data engineering automation
• Experience with monitoring and alerting frameworks for data pipeline reliability