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Data Engineer, Global Planning, Amazon Leo

Job in Bellevue, King County, Washington, 98009, USA
Listing for: Amazon Inc.
Full Time position
Listed on 2026-10-18
Job specializations:
  • IT/Tech
    Data Engineering, Data Warehousing, Data Analyst
Salary/Wage Range or Industry Benchmark: 132100 - 178800 USD Yearly USD 132100.00 178800.00 YEAR
Job Description & How to Apply Below
Data Engineer, Global Planning, Amazon Leo

Amazon Leo is Amazon's low Earth orbit satellite network. Our mission is to deliver fast, reliable broadband connectivity to customers beyond the reach of existing networks. From households to small businesses, schools, hospitals, and government agencies, Amazon Leo will serve communities and organizations operating in places without dependable internet access.

Key job responsibilities
  • Develop Leo data products, infrastructure and ETL pipelines to ingest, parse and transform Geospatial datasets from external & internal APIs using AWS big data technologies (Glue, S3, Redshift, MWAA, EMR, Data Zone, Lambda, etc.)
  • Work alongside Data Scientists, Applied Scientists, Software Engineers and Simulation Engineers to develop appropriate data assets for statistical modeling, system integration and capacity simulations
  • Improve existing solutions and come up with next generation Leo's Data Architecture to improve scale, quality and performance
  • Implement data governance best practices to ensure data accuracy, consistency, and compliance with security and privacy regulations.
  • Develop and maintain scripts to automate processes to generate structured datasets for forecasting plans and system inputs, with focus on efficiency and scalability
  • Build data dictionary, catalog and governance plan and manage and audit all of the registered data via internal mechanisms
  • Provide technical guidance and support to data consumers to leverage Global Planning data assets
Export Control Requirement

Due to applicable export control laws and regulations, candidates must be a U.S. citizen or national, U.S. permanent resident (i.e., current Green Card holder), or lawfully admitted into the U.S. as a refugee or granted asylum.

About the team

Amazon Leo Global Planning team designs and builds systems that support forecasting, management and optimization of Leo's demand, bandwidth capacity and physical inventory across customer segments and channels, worldwide.

Basic Qualifications
  • 3+ years of data engineering experience
  • 1+ years of developing and operating large-scale data structures for business intelligence analytics using ETL/ELT processes experience
  • 1+ years of developing and operating large-scale data structures for business intelligence analytics using OLAP technologies experience
  • 1+ years of developing and operating large-scale data structures for business intelligence analytics using data modeling experience
  • 1+ years of developing and operating large-scale data structures for business intelligence analytics using SQL experience
Preferred Qualifications
  • Experience with AWS technologies like Redshift, S3, AWS Glue, EMR, Kinesis, Fire Hose, Lambda, and IAM roles and permissions
  • Experience with non-relational databases / data stores (object storage, document or key-value stores, graph databases, column-family databases)

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 interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.

Preferred Qualifications
  • Experience with AWS technologies like Redshift, S3, AWS Glue, EMR, Kinesis, Fire Hose, Lambda, and IAM roles and permissions
  • Experience with non-relational databases / data stores (object storage, document or key-value stores, graph databases, column-family…
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