Business Intelligence Engineer, NA Supply Chain Execution- Production Planning Team

About the role

The PPT BI team is the analytics function within North America Supply Chain's production planning organization. We build data pipelines, automated reports, and self service dashboards that help planners and operations leaders make workforce and capacity decisions across a large network of fulfillment and sort centers. We are a small team with high ownership where you operate end to end - from requirements to production. You will partner with operations, staffing, network design, and regional planning teams on work that directly influences how labor is allocated across the network.

Requirements

• 2+ years of analyzing and interpreting data with Redshift, Oracle, NoSQL etc. experience
• Knowledge of BI analytics, reporting or visualization tools like Tableau, AWS QuickSight, Cognos or other third-party tools
• Experience gathering business requirements, using industry standard business intelligence tool(s) to extract data, formulate metrics and build reports
• Knowledge of how to improve code quality and optimizes BI processes (e.g. speed, cost, reliability)
• Master's degree or above in statistics, business analytics, data analytics, data science, computer science or related field
• Experience in designing and implementing custom reporting systems using automation tools
• Experience with statistical analysis, co-relation analysis
• Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.
• Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodatio

Additional Information

Amazon's North America Supply Chain moves millions of packages every day through a network of over 300 fulfillment and sort centers. The Production Planning team is responsible for deciding how many people we need, where we need them, and when - across every site, every shift, every week. Getting this right means customers get packages on time. Getting it wrong means millions in wasted labor or missed delivery promises. We are looking for a Business Intelligence Engineer who will build the analytics backbone that powers these planning decisions. You will not just write queries and build dashboards. You will own the data infrastructure that hundreds of planners and operators rely on every single week to make headcount and capacity decisions across the network. Your work will directly influence how Amazon allocates tens of thousands of labor hours and millions of dollars in workforce spend. This is a high ownership role. You will take ambiguous business questions, figure out where the data lives, build the pipeline to transform it, deliver it in a format stakeholders can act on, and then measure whether it actually drove better decisions. You will operate at the intersection of data engineering, business intelligence, and operational planning at a scale few companies can offer. Key job responsibilities Own the development and maintenance of dashboards and automated reports that surface critical production planning metrics to stakeholders across the NASC network. Collaborate with cross functional business teams including NASC Operations, Workforce Staffing, Network Design and Planning, and Regional Planning to translate workforce planning questions into analytical frameworks and deliver actionable insights that drive real decisions. Design, build, and deploy data pipelines using Python, SQL, AWS Lambda, Athena, and Redshift. Monitor pipeline health proactively. Ensure reliable and timely data delivery aligned to weekly planning cadences where a one day delay means planners are flying blind. Build and maintain curated datasets that serve as the single source of truth for capacity planning across the network. This includes a centralized data lake with well defined schemas, partition strategies, lineage documentation, and freshness SLAs that multiple downstream consumers depend on. Identify and implement automation opportunities that reduce manual data processing. Every hour a planner spends pulling data manually is an hour they are not spending on strategic planning decisions. Your job is to eliminate that waste through scalable self service solutions. Maintain clear documentation of data sources, business logic, transformation rules, and dataset schemas. A day in the life You start the morning checking pipeline health and resolving any data quality alerts. Mid morning you join a planning standup to scope a new analytics request from operations leadership. After lunch you build or refine an interactive dashboard based on stakeholder feedback, adding features like drill downs and exports on the spot. In the afternoon you collaborate with cross functional partners to validate a dataset powering planning decisions. You close the day committing code, documenting transformation logic, and identifying the next automation opportunity.

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