Data Engineer II — Space Broadband Data Platform

Amazon Inc.; Omaha, Northern (NE, KY); Hybrid; USD 132,000 - 179,000; Full time

Job summary

Amazon Leo is building a cloud data infrastructure for its airborne broadband initiative. A Data Engineer will design and implement ETL/ELT pipelines, data models and warehousing strategies to support BI analytics and ML modeling across Leo teams.

You will collaborate with data scientists, software engineers and simulation engineers to craft scalable data assets and governance processes that ensure data accuracy, security and compliance in a fast-moving pre-launch environment.

Qualifications

• 3+ years data engineering experience.
• 1+ years developing and operating ETL/ELT pipelines for BI analytics.
• 1+ years developing and operating large-scale data structures using SQL and data modeling.

Responsibilities

• Develop Leo data products, infrastructure and ETL pipelines for geospatial datasets using AWS big data technologies.
• Collaborate with data scientists and engineers to build data assets for modeling and simulations.
• Improve data architecture for scale, quality and performance.
• Implement data governance to ensure accuracy, consistency and security.
• Automate processes to generate structured datasets for forecasting POR and system inputs.
• Create and audit data dictionaries, catalogs and governance plans.

Skills

Data engineering

ETL/ELT

SQL

Data modeling

OLAP technologies

Warehouse design

Oracle experience

Education

Bachelor's degree in Computer Science, Engineering, Information Systems, Mathematics, or related field

Tools

AWS Redshift

AWS S3

AWS Glue

AWS EMR

Kinesis

Lambda

IAM

MWAA

Data Zone

Oracle

Job description

Amazon Leo is building a cloud data infrastructure for its airborne broadband initiative. A Data Engineer will design and implement ETL/ELT pipelines, data models and warehousing strategies to support BI analytics and ML modeling across Leo teams.

You will collaborate with data scientists, software engineers and simulation engineers to craft scalable data assets and governance processes that ensure data accuracy, security and compliance in a fast-moving pre-launch environment.