R Shiny Developer

We are seeking a skilled R Shiny Developer to join our data engineering and analytics team. The ideal candidate will have a strong background in R programming, data handling, and visualization. You will be responsible for building and deploying interactive web applications using R Shiny, focused on data-driven insights and analytics. While no specific business knowledge is required, familiarity with the pharmaceutical industry is a plus. Key Responsibilities: Develop and Deploy Applications: Design, develop, and maintain interactive web applications using R Shiny. Ensure that applications are scalable, secure, and optimized for performance. Data Engineering and Management: Handle large datasets, ensuring data integrity and quality. Collaborate with data engineers to extract, transform, and load (ETL) processes for datasets used in R Shiny applications. Data Visualization and Analytics: Create interactive dashboards and visualizations that effectively communicate data insights. Utilize R and other tools to perform data analysis and generate reports. Collaboration and Communication: Work closely with data scientists, analysts, and other stakeholders to understand requirements and deliver high-quality solutions. Participate in team meetings and contribute to project planning and timelines. Documentation and Best Practices: Document all stages of the application development process. Adhere to best practices in coding, version control, and testing. Qualifications Education: Bachelor’s or Master’s degree in Computer Science, Data Science, Statistics, or a related field. Technical Skills: Strong proficiency in R programming and experience with R Shiny. Experience with data manipulation tools (e.g., dplyr, tidyr) and data visualization libraries (e.g., ggplot2, plotly). Familiarity with SQL and database management. Understanding of web technologies (HTML, CSS, JavaScript) is a plus. Experience with Git or other version control systems. Experience: Proven experience in developing and deploying R Shiny applications. Experience in data engineering, including ETL processes. Experience with cloud platforms (e.g., AWS, Azure) is desirable. Soft Skills: Strong problem-solving skills and attention to detail. Ability to work independently as well as part of a team. Good communication skills, with the ability to present technical information to non-technical stakeholders. Preferred Qualifications: Experience in the pharmaceutical industry or familiarity with healthcare data. Knowledge of machine learning or advanced analytics. Experience with other programming languages such as Python.