Data Engineer

Responsiblties:

• Define operational procedures and practices.
• Work cross-organizationally to facilitate widespread use and adoption of the AWS and/or Azure platforms, and developing a deep expertise in the AWS/Azure technologies broad knowledge around how applications and services are constructed using the AWS/Azure platform.
• Coordinate and/or complete the development of all necessary design documentation associated with cloud service solutions.
• Educate customers on the value proposition of AWS, and participate in architectural discussions to ensure solutions are designed for successful deployment in the cloud.
• Develops high level functional and technical design specifications into design for web applications using SOA, Micro services and container technologies.
• Provide Consultancy and architecture support for Application migration to public and private cloud.
• Engages in developing proof of concepts (POCs) for new projects, assessment for cloud amenability and create business case.
• Drives engineering processes for the project such as building applications for Cloud  build automation, unit testing, software configuration management and creating logical and deployment architecture for cloud.
• Create best practices / technical guidelines for building & hosting applications in private & public cloud environment.

Qualification:

• Must have an active DoD secret security clearance.
• BA/BS degree or higher in Computer Science or Information Systems.
• 6-8 years of experience in some or all the following areas: software development, application architecture, technical architecture, requirements development, requirements management, design methodologies, DevSecOps, CI/CD, agile development methodologies, application integration, high availability, application performance, test automation, serverless, microservices, containerization, monitoring, instrumentation, observability, etc.
• 2+ Years of Experience with software development and application migration in cloud environments.

Key Skills:

• Data warehousing. 
• Knowledge of operating systems. 
• Database systems. 
• Data analysis.
• Critical thinking skills.
• Basic understanding of machine learning. 
• Communication skills.