R Analytics Cloud Engineer

Job Description:
Data Engineering and Advance Analytics Enablement team is looking for a R Analytics Cloud Engineer that will be playing a key role in helping on enabling Analytics Tools for client’s research community and supporting Analytics application migration to Cloud and bring in key transformational changes to how we deploy Analytics Tools using cloud native architecture.

Duties & Responsibilities:
Assess, design, and build workflows to integrate solutions for scalable, reliable, and automated “R” analytics data science products on AWS
Develop data science tool with R Shiny as the web framework and deploy the artifacts into RStudio Connect via CI/CD.
Design, develop, test, and support R programs to execute modeling application systems via distributed computing on AWS
Support business applications in deploying models into the cloud with containerization technologies such as Docker and Kubernetes
Support the team in the writing of deployment scripts and place a strong emphasis on automated deployment, infrastructure automation solutions, and continuous delivery processes
Leverage Analytics Data Platform tools (RStudio on Domino/Sagemaker, RStudio Connect), AWS services to build workflows that will support deployment of analytics applications developed in R
Participate in an on-call rotation for critical outages and issues
Strong hands-on working experience with Shell Scripting (Bash, Csh, Ksh)
Effective communication and technical skills
Develop & maintain technical documentation including system diagrams & operational procedures

Required qualifications:
Experience in IT related experience including software development, Data Scientists & DevOps functions.
Solid development experience in R, R packages, RStudio, RStudio Connect, RStudio Package Manager, Python, SQL, Web & Cloud Technologies
Experience with AWS services supporting data science and analytics (EC2, S3, RDS, Lambda, Sagemaker, Glue)
Experience in an analytical role involving data extraction, analysis, and communication of findings
Experience in building and maintaining CI/CD tooling (Jenkins, Bitbucket Pipelines, GitHub).
Experienced in Data Exploration packages with Base R
Experienced in using deep learning frameworks such as TensorFlow, Pytorch, etc.
Ability to effectively communicate technical solutions to engineering teams and business audiences

Key Competencies:
· Knowledgeable in the AWS Well Architected Framework
· Strong analytical, organizational, problem-solving, and time-management skills
· Strong communication (verbal and written) and listening skills.
· Strong teamwork, planning, and coordination skills
· Self-motivation, adaptability, and the ability to meet aggressive deadlines.
· Ability to independently research and resolve technical problems in a complex IT environment with local and remote groups.