Software Development Engineer II , Amazon Fulfillment Technologies - Inbound
Role Overview
Amazon Fulfillment Technologies Inbound builds systems that move inventory into Amazon's fulfillment network.
The engineer owns large-scale data infrastructure supporting decisions across the inbound supply chain.
The work combines data engineering with production ML workflows at petabyte scale.
Key Skills for This Role
Full Job Posting
Role overview
Amazon Fulfillment Technologies Inbound builds systems that move inventory into Amazon's fulfillment network.
The engineer owns large-scale data infrastructure supporting decisions across the inbound supply chain.
The work combines data engineering with production ML workflows at petabyte scale.
Key responsibilities
- Build and operate reliable batch and streaming pipelines for supply-chain data.
- Own data models, warehouses, and curated datasets for analytics, reporting, and ML.
- Build feature engineering pipelines and feature stores.
- Lead design reviews and technical trade-offs for owned systems.
- Own data quality, lineage, observability, and reliability improvements.
- Partner with scientists on feature delivery, training data, and model-scoring workflows.
- Deliver tested production software and support CI/CD, monitoring, and operational excellence.
- Troubleshoot production and data issues, participate in on-call, and automate operational work.
- Mentor early-career engineers and influence the data platform roadmap.
Basic qualifications
- At least 3 years building complex software systems.
- Bachelor's degree in Computer Science, Engineering, Mathematics, or a related field.
- Strong Python proficiency and SQL experience at scale.
- Production experience owning batch and streaming data pipelines.
- Experience with Spark, Hive, Presto, or similar distributed frameworks.
- Experience with data models and ETL/ELT for analytics, reporting, and ML workloads.
- Experience collaborating with science or ML teams to productionize models.
- Experience with production data quality, validation, or observability.
- Experience using AI coding assistants or agentic development tools.
- Software engineering fundamentals including testing, CI/CD, code review, and production operations.
Preferred qualifications
- Production ML deployment and large-scale data architecture experience.
- MLOps tools such as SageMaker Pipelines, Step Functions, or MLflow.
- Cross-team ML-integrated service delivery, agentic workflows, prompt engineering, or LLM APIs.
- ML evaluation frameworks, data lineage, cataloging, and observability tools.
- Streaming tools such as Kafka, Kinesis, or Flink; orchestration tools such as Airflow or AWS Glue workflows.
- Infrastructure as code, business reporting infrastructure, or supply-chain, logistics, fulfillment, or operations experience.
About the team
The team builds software and science for inventory movement from supplier shipment through receipt and stow.
Its systems support a global network handling billions of units and focus on faster, more accurate, cost-efficient inbound flow.
The team partners with Applied and Research Scientists on data engineering and applied ML.
Compensation
- The listed base salary range for Bellevue, Washington is USD 143,700–194,400 annually.
- The package includes sign-on payments and restricted stock units; final compensation depends on experience, qualifications, and location.
- Benefits include insurance, 401(k) matching, paid time off, and parental leave.
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