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indeed

Software Development Engineer II , Amazon Fulfillment Technologies - Inbound

Amazon.com
Bellevue, USA
Full-time
Onsite
USD 143700-194400 yearly
Discovered 3 weeks ago
PythonSQLBatch and streaming data pipelinesSpark, Hive, Presto, or similar distributed computing frameworksData modeling and ETL/ELTMachine learning workflow productionization

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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