Data Engineer II, AWS Infrastructure Supply Chain

Amazon - Arlington, VA

Full-time - Mid Level

Arlington, VA

Sporting Goods, Hobby, Musical Instrument, Book, and Miscellaneous Retailers

About the position

The Data Engineer role within the Manufacturing Operations, Transportation Operations, and Reverse (MOTOR) organization at AWS focuses on supporting the Supply Chain Intelligence team. This position is responsible for connecting various systems across the supply chain to ensure operational teams have access to clean, actionable data. The ideal candidate will work with large volumes of data, tackle complex technical challenges, and be passionate about data and analytics, contributing to the optimization and predictive analysis of data pipelines.

Responsibilities

• Build and maintain the infrastructure to answer questions with data, using software engineering best practices and data management fundamentals.
• Build datasets that analysts and scientists use to generate actionable insights.
• Define data engineering processes leveraging various AWS services to improve data accessibility, redundancy, integrity, cost, and storage.
• Develop high-quality solutions for scalable product/model development that meets business needs while anticipating future requirements.
• Collaborate with various teams to understand business and technical requirements and make decisions that enhance product/program efficiency.
• Interface with other technology/data engineering teams to extract, transform, and load data from diverse sources using AWS data technologies.
• Lead the technical design and implementation of the data infrastructure.
• Design and manage data audit, quality, and reconciliation processes in collaboration with stakeholders.

Requirements

• Bachelor's degree
• 3+ years of data engineering experience
• Experience in at least one modern scripting or programming language such as C++, C#, Java, Python, Scala, Golang, PowerShell, SQL, Ruby, or NodeJS.

Nice-to-haves

• 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 building/operating highly available, distributed systems for data extraction, ingestion, and processing of large datasets
• Experience with big data technologies such as Hadoop, Hive, Spark, EMR.

Benefits

• Flexible working culture
• Employee-led affinity groups
• Ongoing events and learning experiences
• Mentorship and career-advancing resources