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Business Intelligence Engineer, North America Transportation Services
Amazon
On-sitemidPosted May 5, 2026
About the Role
Develop and maintain dashboards and reports for transportation metrics, design and deploy data pipelines and models, and create curated datasets to support both analytical needs and machine learning models.
Requirements
Requires a Business Intelligence Engineer to build end-to-end analytics solutions for Amazon's transportation network, including dashboards, data pipelines, and curated datasets, to provide insights for operational decisions and power machine learning models.
Full Job Description
Amazon delivers billions of packages each year through one of the world's most complex transportation networks. As a Business Intelligence Engineer on our North America transportation analytics team, you will build the dashboards, data pipelines, and curated datasets that help operators and planners move packages faster, more accurately, and at lower cost — from fulfillment centers through middle mile hubs to customers' doors.
You will own analytics solutions end-to-end: partnering with business teams to define the right questions, engineering the data infrastructure to answer them, and delivering insights that drive real operational decisions. You will also build purpose-built datasets that power machine learning models for demand forecasting, route optimization, and capacity planning — giving you direct exposure to applied AI in a production logistics environment.
Key job responsibilities
- Own the development and maintenance of dashboards, reports, and visualizations that surface critical transportation metrics — including capacity constraints, route performance, forecast accuracy, and operational bottlenecks — to stakeholders across the transportation network
- Collaborate with cross-functional business teams spanning network design, planning, delivery operations, and linehaul to translate operational questions into analytical frameworks and deliver actionable insights
- Design, build, and deploy data pipelines, data models, and SQL-based transformations to support analytical and reporting needs; monitor pipeline health proactively and resolve data quality issues to ensure reliable, timely data delivery
- Develop and maintain curated, well-documented datasets purpose-built for AI and machine learning models supporting demand forecasting, route optimization, and capacity planning — ensuring standards for completeness, accuracy, freshness, schema consistency, and lineage tracking
- Maintain clear documentation of data sources, business logic, transformation rules, and dataset schemas; identify and implement automation opportunities to reduce manual data processing tasks
A day in the life
You start the day reviewing pipeline health dashboards and resolving any overnight data quality alerts. Mid-morning, you join a standup with the NATS Planning team to discuss a new capacity forecasting request — you scope the requirements and outline a delivery timeline. After lunch, you refine a QuickSight dashboard that tracks route-level performance for AMZL operations managers, incorporating feedback from last week's review. In the afternoon, you collaborate with an Applied Scientist to validate a curated dataset powering a demand forecasting model, ensuring schema consistency and data freshness meet the team's SLA. You close the day by committing pipeline code updates to your team's repository and documenting the transformation logic for a new data mode
About the team
North America Transportation Services (NATS)
Formally known as NA Transportation Outbound Execution, NATS manages the design, speed, and connectivity of Amazon's outbound transportation network. The organization owns the journey of packages from Fulfillment Center (FC) outbound docks through middle mile connections and into final mile delivery, working with both internal and external carriers to optimize package delivery.
NATS serves as the "steward of the network," ensuring all decisions on transportation capacity and carriers are in the best interest of Amazon as a whole, working to break down silos among teams.
You will own analytics solutions end-to-end: partnering with business teams to define the right questions, engineering the data infrastructure to answer them, and delivering insights that drive real operational decisions. You will also build purpose-built datasets that power machine learning models for demand forecasting, route optimization, and capacity planning — giving you direct exposure to applied AI in a production logistics environment.
Key job responsibilities
- Own the development and maintenance of dashboards, reports, and visualizations that surface critical transportation metrics — including capacity constraints, route performance, forecast accuracy, and operational bottlenecks — to stakeholders across the transportation network
- Collaborate with cross-functional business teams spanning network design, planning, delivery operations, and linehaul to translate operational questions into analytical frameworks and deliver actionable insights
- Design, build, and deploy data pipelines, data models, and SQL-based transformations to support analytical and reporting needs; monitor pipeline health proactively and resolve data quality issues to ensure reliable, timely data delivery
- Develop and maintain curated, well-documented datasets purpose-built for AI and machine learning models supporting demand forecasting, route optimization, and capacity planning — ensuring standards for completeness, accuracy, freshness, schema consistency, and lineage tracking
- Maintain clear documentation of data sources, business logic, transformation rules, and dataset schemas; identify and implement automation opportunities to reduce manual data processing tasks
A day in the life
You start the day reviewing pipeline health dashboards and resolving any overnight data quality alerts. Mid-morning, you join a standup with the NATS Planning team to discuss a new capacity forecasting request — you scope the requirements and outline a delivery timeline. After lunch, you refine a QuickSight dashboard that tracks route-level performance for AMZL operations managers, incorporating feedback from last week's review. In the afternoon, you collaborate with an Applied Scientist to validate a curated dataset powering a demand forecasting model, ensuring schema consistency and data freshness meet the team's SLA. You close the day by committing pipeline code updates to your team's repository and documenting the transformation logic for a new data mode
About the team
North America Transportation Services (NATS)
Formally known as NA Transportation Outbound Execution, NATS manages the design, speed, and connectivity of Amazon's outbound transportation network. The organization owns the journey of packages from Fulfillment Center (FC) outbound docks through middle mile connections and into final mile delivery, working with both internal and external carriers to optimize package delivery.
NATS serves as the "steward of the network," ensuring all decisions on transportation capacity and carriers are in the best interest of Amazon as a whole, working to break down silos among teams.