Data Engineer II, Amazon Leo

Full Job Description

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.

As a Data Engineer in Leo's Global Business Operations (GBO), you will be one of the architects and engineers building up the cloud data infrastructure for use across Leo. You will be working directly on AWS to build internal tools used across the hundreds of Business Intelligence Engineers and Scientists to build business-critical reports and ML Models. You will design the data models used by these teams to efficiently dive deep into the business and extract insights. Getting in pre-launch, you have creative influence to drive this engineering direction on a native stack and your outputs will be critical to the success of Leo's ambitious mission.

Key job responsibilities In this role, you will:

• 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 POR 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

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
• 1+ years of developing and operating large-scale data structures for business intelligence analytics using Oracle experience
• 3+ years of in the job offered or a related occupation experience
• 1+ years of developing and operating large-scale data structures for business intelligence analytics using each of the following: ETL (Extract, Transform, Load)/ELT (Extract, Load, Transform) processes experience
• Bachelor's degree or foreign equivalent in Computer Science, Engineering, Information Systems, Mathematics, or a related field
• Experience with data modeling, warehousing and building ETL pipelines

Preferred Qualifications

• Experience with AWS technologies like Redshift, S3, AWS Glue, EMR, Kinesis, FireHose, 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.

The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits.

USA, VA, Arlington - 132,100.00 - 178,800.00 USD annually

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 1+ years of developing and operating large-scale data structures for business intelligence analytics using Oracle experience 3+ years of in the job offered or a related occupation experience 1+ years of developing and operating large-scale data structures for business intelligence analytics using each of the following: ETL (Extract, Transform, Load)/ELT (Extract, Load, Transform) processes experience Bachelor's degree or foreign equivalent in Computer Science, Engineering, Information Systems, Mathematics, or a related field Experience with data modeling, warehousing and building ETL pipelines