The Amazon Selling Partner Trust & Store Integrity Science Team is seeking a data engineer to build robust data platforms and pipelines that support machine learning systems. This role involves designing and maintaining scalable data infrastructure to process large volumes of data, ensuring data integrity and reliability. The engineer will collaborate with scientists to translate research into production-ready systems, directly impacting the safety of millions of transactions. The position offers the opportunity to work in a diverse team environment focused on preventing eCommerce fraud.

• 3+ years of data engineering experience
• 1+ years of experience developing and operating large-scale data structures for business intelligence analytics using ETL/ELT processes
• 1+ years of experience with OLAP technologies
• 1+ years of experience with data modeling
• 1+ years of experience using SQL
• 1+ years of experience using Oracle
• Experience with AWS technologies such as Redshift, S3, AWS Glue, EMR, Kinesis, FireHose, Lambda, and IAM roles
• Experience with non-relational databases or data stores

• Design, build, and maintain scalable data pipelines that support multiple ML model training and inference workflows
• Develop and optimize ETL processes to ingest, transform, and prepare terabytes of data from diverse sources for model consumption
• Implement robust data quality checks and monitoring systems to ensure data integrity across all pipelines
• Build and maintain infrastructure for model training pipelines, including feature engineering, data versioning, and experiment tracking
• Design and implement scalable inference pipelines that serve predictions for millions of transactions with low latency and high reliability
• Collaborate with scientists to productionize ML models, translating research code into production-ready systems
• Optimize data processing workflows for cost efficiency and performance, managing compute and storage resources effectively
• Implement monitoring, alerting, and logging systems to ensure pipeline reliability and quick issue resolution
• Maintain comprehensive documentation of data schemas, pipeline architectures, and operational procedures
• Partner closely with scientists to understand data requirements and translate them into technical solutions
• Work with stakeholders to define data SLAs and ensure systems meet business needs
• Provide technical guidance on data architecture decisions and best practices

• Employees at Amazon are often offered comprehensive health benefits—including multiple medical plan options (no pre-existing condition exclusions, 100% covered in-network preventive care), dental and vision plans, a 24/7 medical advice line from day one, expert second-opinion services, and broad mental-health support with several free counseling sessions (including pediatric). Financial wellness typically includes a 401(k) with company match (up to 2%), Restricted Stock Units (equity), FSAs, an emergency savings program, product and partner discounts, and even college-savings and home-purchase programs. Overall, the package is designed to support employees and their families’ health, finances, and day-to-day life.