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Amazon · 3 days ago

Data Engineer

Bellevue, WA

Full-time

Onsite

Mid Level

$119K/yr - $206K/yr

3+ years exp

Amazon is an initiative to increase global broadband access through a constellation of satellites. As a Data Engineer in Leo's Global Business Operations, you will build cloud data infrastructure, develop ETL pipelines, and design data models to support business intelligence efforts.

Artificial Intelligence (AI)DeliveryE-CommerceFoundational AIRetail

No H1B

U.S. Citizen Only

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 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

Qualification

Data engineering experienceAWS technologiesETL pipelinesData modelingNon-relational databasesSQL coding

Required

3+ years of data engineering experience

Experience with data modeling, warehousing and building ETL pipelines

Bachelor's degree

Preferred

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)

Experience in data warehouse technical architectures, data modeling, infrastructure components, ETL/ ELT and reporting/analytic tools and environments, data structures and hands-on SQL coding