DotNet Developer

Participate in the planning and analysis for each release Involve in the design aspects as it relates to application development/enhancements and future stability/sustainability of the application

Responsible for supporting the team (business analysts, quality assurance analysts, project manager, other developer, etc.) as it relates to application development changes and integration with other IT partner deliverables Engaging in the application development for releases to provide enhanced capabilities and functionality to the application Dealing with post release support, incident ticket resolution, and ad-hoc business requests

Participate in the daily standup and provide status updates, contribute to team meetings Provide and recommend innovative solutions to complex issues Develop proof-of-concept prototypes in support of future product concepts

 

Qualifications

4+ years of extensive comprehension and hands on experience in developing and supporting enterprise applications Full stack development experience required (in Microsoft technologies) NET MVC / .NET Core Services / any JS UI Framework SQL Server Using and configuring Dev-Ops tools such as Jenkins, SVN, GIT etc. Preferred Knowledge on IOT Preferred Preferred having worked in JS Frameworks such as Angular / React with .NET Worked in agile development methodologies

A good understanding of the Applications Lifecycle Management (ALM), with full lifecycle experience, from design through to development, testing and deployment A good understanding over extreme programming/practices such as Continuous Integration, Continuous Deployment, Pair programming, Test Drive Development Experience with both non-Agile and Agile processes Experience with common enterprise security protocols Have excellent interpersonal, verbal and written communication skills

 

Desired Skills

Good to have Microsoft Azure Experience Good to have Business Intelligence and Reporting skills (SSAS, SSIS, SSRS) Knowledge of SharePoint and Microsoft big data tools such as Stream Analytics and Machine Learning