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Senior Business Intelligence Engineer, Devices Supply Chain Technology

External
Amazon.com Services LLC logoAmazon.com · Sunnyvale, CA
Full-timeOn-site2d ago
PythonSQLAWS
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About the role

Devices Supply Chain Technology is the team that brings Amazon Devices supply chain's data, analytics, and tools together in one place. We build what our supply chain, finance, operations, and program teams rely on to make decisions. We use AI to build faster, and we design our products so AI agents and people can both use them. We value ownership, high standards, and building with our business partners.

Requirements

  • 10+ years of professional or military experience
  • 5+ years of SQL experience
  • Experience in scripting for automation (e.g. Python) and advanced SQL skills.
  • Experience with AWS technologies
  • Experience with data visualization using Tableau, Quicksight, or similar tools
  • Experience with data modeling, warehousing and building ETL pipelines
  • Experience building data products incrementally and integrating and managing data sets from multiple sources
  • Experience in supply chain such as contracting, demand management and/or planning and procurement, and supply chain operations
  • Experience working directly with business stakeholders to translate between data and business needs
  • Experience working with large, complex data sets
  • Experience managing, analyzing and communicating results to senior leadership
  • Master's degree or equivalent in a quantitative field such as statistics, mathematics, data science, business analytics, economics, finance, engineering, or computer science
  • 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 accommodation or adjustment during the application and hiring process, including support for the in

Additional Information

At Amazon Devices, the teams behind products like Kindle and Echo make sourcing and cost decisions across thousands of components and hundreds of programs. This role builds and maintains the data foundation those decisions depend on. We are looking for a Senior Business Intelligence Engineer to build and run the core data foundation, and turn the data into the metrics and diagnostics leaders act on. You will create the pipelines and data models behind those metrics, and develop the analytics that explain not just what happened but why. You will design the data layer to be consumed by people and AI agents alike. This is a build role with ambiguity: problems arrive loosely defined, and you turn them into reliable data and clear answers. Key job responsibilities - Build and own the core data pipelines and data models for supply chain cost, commodity, and sourcing metrics, including data that comes from suppliers. - Work with business owners across sourcing, operations, finance, and program teams to turn analysis and diagnostics into decisions. - Establish data standards (taxonomies, reference data, schema governance) so metrics and reporting reconcile to one source. - Make the data layer machine-readable and agent-ready, and automate recurring narratives and reviews with LLMs and agentic patterns where they earn their place. - Build in data quality: traceable lineage, validation, anomaly detection, and monitoring. - Partner with central Data Engineering to scale governed, automated pipelines across the organization. - Set the technical standards other teams can adopt for working with supply chain data, and mentor engineers and analysts. A day in the life You take on problems that arrive loosely defined. Working with the business owners who bring in the supplier data and act on the result, you trace where it comes from, pin down the source of truth, and build the pipeline and data model behind it. You turn that into the metrics and dashboards that move a decision. The payoff is a source other teams can trust and build on. You move fast, handle shifting priorities, and leave the data better than you found it.


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