The Software Development Engineer II role at Amazon Fulfillment Technologies focuses on building large-scale data infrastructure to enhance decision-making in the inbound supply chain. The team is responsible for developing data pipelines, models, and processing systems that manage vast amounts of supply-chain data. This position requires collaboration with Applied and Research Scientists to integrate Machine Learning systems into the data workflows. The ideal candidate will have a strong background in data engineering and a passion for optimizing data processes at scale.

• 3+ years of building complex software systems experience
• Bachelor's degree in Computer Science, Engineering, Mathematics, or a related field
• Strong Python proficiency and experience with SQL at scale
• Experience building and owning batch and streaming data pipelines in production environments
• Experience with big data technologies such as Spark, Hive, or Presto
• Experience building data models and ETL/ELT pipelines for analytics and ML workloads
• Experience collaborating with science or ML teams to productionize models
• Experience with data quality, validation, or observability practices
• Experience deploying ML models to production environments
• Experience designing and optimizing large-scale data architectures
• Experience with MLOps tooling for operationalizing model workflows
• Experience with streaming data processing technologies like Kafka or Kinesis
• Experience with data orchestration tools such as Airflow or AWS Glue
• Experience with infrastructure-as-code tools like CDK or Terraform
• Background in supply-chain, logistics, fulfillment, or operational environments

• Independently design, build, and operate scalable data pipelines that serve large volumes of supply-chain data.
• Own data modeling, data warehousing, and the design of curated datasets for analytics and ML use cases.
• Build and maintain feature engineering pipelines that supply ML models with high-quality data.
• Lead design reviews and make technical trade-offs across performance, cost, and scalability.
• Ensure data quality, lineage, and observability across datasets and pipelines.
• Partner with scientists to operationalize ML workflows including feature delivery and model scoring.
• Deliver robust, production-quality software and drive engineering best practices.
• Diagnose and resolve complex production and data issues while participating in on-call duties.
• Mentor early-career engineers and influence the technical roadmap for the team's data platform.

• 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.