Spearhead enterprise integration of marketing platform using MuleSoft & Salesforce. Lead enterprise wide transformation of CRM platform to create the migration strategy.
• Research & provide best custom cloud solutions for the current infrastructure. Implement the cloud integration for ERP, CRM, e-Commerce, or mobile (Salesforce, NetSuite, Oracle, SAP, Workday, Ariba, etc.)
• Strategic planning and review existing architecture planning on enhancement and changes to improve the organization operational efficiency. Analyze, risk assess and document risk mitigations with the risk management team.
• Determine research objectives, work with the executive team to improve the customer acquisition/retention by applying CRM doctorate level research.
• Use predictive analytics, deep learning and machine learning techniques to identify and prevent cyber threats, improve product line sales and CRM customer marketing strategies.
• Orchestrate information technology strategies and implement technological strategic solutions from academic experience by ensuring best possible designs (performance, scalability) of MuleSoft applications/ solution compliance with MuleSoft best practices, coding standards in accordance to corporate standards.
• Research and improvise current SDLC lifecycle to reduce go-to-market time and deploy periodic release of quality products. Implement end-to-end continuous delivery and continuous integration, design architecture, development, test and deployment of CRM, ERP and HCM platforms.
• Track emerging technologies, evaluate and improvise architecture to meet business goals and operational.
• Oversee scrum ceremonies using agile manifesto for continuous delivery and provide suggestions to improvise safe scrum practices.
• Analyze web services interoperability, criticize and formulate solutions in multi-vendor and architecture committee meetings. Responsible for communication, collaboration with stakeholders, document and implement best practices.
• Identify project goals, research methods, choose right data collection techniques, identify target audience to increase ROI of product deliveries.
• Implement statistical and data mining techniques e.g hypothesis testing, machine learning and retrieval processes on a large amount of data to identify trends, patterns and other retrieval information.
• Perform data modelling using advanced statistical analysis, unstructured data processing and develop predictive models, support/mentor product team members.
Educational requirements : Masters’ in IT and preferably undergoing PHD or Doctrate program
|Job Category||Full Time|