AWS Solution Architect

Job Description

We have a position for a AWS Solution Architect with one of our clients in Atlanta, GA for an initial contract duration of 6 months. No third party candidates considered for this position.

We offer opportunities for career growth at one of the largest, financially stable companies in the world.

A Day In The Life Typically Includes:

We are seeking an experienced hand on Solution Architect to lead the development, implementation and on-going governance of our future Enterprise Data Lake and data analytics architecture and related platforms. This role will be a member of the Enterprise Data and Advanced Analytics team that provides enablement for advanced analytics throughout the company by efficient ingest, storage and consumption of data both manufacturing and commercial as well enables data science model management, deployment and monitoring for various customer groups.

Responsibilities:

• Provide technical leadership for data analytics architecture and platform decisions for the enterprise data and analytics team.
• Collaborate with technology and business resources to understand the company’s data environment, analytics business opportunities and overall analytics processing requirements. 
• Develop and implement a future-state data analytics architecture and platform standards-roadmaps for both the back-end data processing and the front-end data visualization/statistical components.
• Leverage public cloud and open standards technologies in architecting future data and analytics platforms
• Partner with Enterprise Architecture team to implement new data and analytics platforms especially those utilizing AWS technologies such as EMR, Redshift, Kinesis and associated technologies.
• Implement real time streaming, batch and near real time data movement design patterns, lead a team of engineers in best practices in ELT and data storage.
• Work with Data science and data engineering teams to experiment and prove out new technologies enabling new capabilities.
• Provide guidance to data scientists in efficient model creation, deployment and management. Participate in projects across the business and IT team in platform evaluations as well software selection process.