Data Engineer, Seller Partner Trust and Store Integrity Science

Amazon • Seattle, WA

43d • Onsite

About The Position

We are looking for a talented data engineer who is passionate about building robust data platforms and pipelines that empower scientists to develop advanced machine learning systems, helping manage the safety of millions of transactions every day and scaling up our operations with automation.

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 experience
• 1+ years of developing and operating large-scale data structures for business intelligence analytics using OLAP technologies experience
• 1+ years of developing and operating large-scale data structures for business intelligence analytics using data modeling experience
• 1+ years of developing and operating large-scale data structures for business intelligence analytics using SQL experience
• 1+ years of developing and operating large-scale data structures for business intelligence analytics using Oracle experience
• Experience with data modeling, warehousing and building ETL pipelines

Nice To Haves

• Experience with AWS technologies like Redshift, S3, AWS Glue, EMR, Kinesis, FireHose, Lambda, and IAM roles and permissions
• Experience with non-relational databases / data stores (object storage, document or key-value stores, graph databases, column-family databases)

Responsibilities

• 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

Benefits

• health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage)
• 401(k) matching
• paid time off
• parental leave
• sign-on payments
• restricted stock units (RSUs)

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Education Level: No Education Listed