Salesforce Architect

Job Description

Technical Expertise:

• Strong hands-on experience architecture in cloud technologies. Salesforce is required, and other clouds is preferable.
• Ability to understand E2E objective, business problem and drive technology architecture to solve business problems with customer first mindset.
• Understanding of Analytics / Artificial Intelligence / Data Science use cases and corresponding data sets to propose scalable architecture.
• Collaborate with team of technical experts to build prototypes, pilots, and drive new technology adoption and delivery excellence.
• Specification, design, implementation, test, validation, and industrialization of advanced data management, artificial intelligence and analytic functions to be incorporated in products, systems and solutions.
• Contributions to the identification and evaluation of potential external partners;
• Collaborate with product managers of technology providers (Salesforce and others) to share feedback paving way for future evolution of products.
• Contributions to intellectual property protection, capitalization of knowledge, and internal and external communication on Analytics / Artificial Intelligence / Data Science.

Managerial Skills:

• Stakeholder Management
• Design and develop marketing automation solutions using Salesforce Marketing.
• Develop and maintain data models, data flows, and data mappings.
• Develop and maintain marketing automation processes and campaigns.
• Develop and maintain marketing automation workflows.
• Develop and maintain marketing automation reports and dashboards.
• Provide technical guidance and support to other team members.
• Condition monitoring, diagnosis, and maintenance.
• Reliability, Availability, and maintainability, of platform and applications

Qualification:

• Master's or Bachelor or equivalent diploma in Computer Science / IT / Analytics / Artificial Intelligence / Data Science or related subjects, ideally with 5 years of experience in data processing and Analytics / Artificial Intelligence / Data Science model development.
• Strong understanding of Software engineering skills/experience: capacity to perform coding, debugging, testing (including unit tests, functional tests, and integration tests) and troubleshooting throughout the application development process and in agile mode.4
• Orientation towards solving problems, achieving results and applying technology to real-life business cases.
• Effective communication skills including aptitude for data-driven story telling: convincing with words, impacting with data, and influencing with visuals.
• Autonomy AND capacity to cooperate.
• Openness of mind AND scientific rigor.
• Fluent English.
• Some knowledge of Energy Management and Automation markets.