Salesforce Data Cloud Architect

Responsibilities :

Responsible for matching business process and automation requirements to the capabilities of SFDC, including data model, role hierarchy, sharing and security model
Provide functional architecture strategy and guidance for all SFDC rollouts, Design-for-adoption strategy
Designing the overall data architecture, using Salesforce Data Cloud as the central repository to support Customer 360 Data Manager, ensuring all customer data is consolidated and actionable.
Reviews functional design for initiatives and lead defining dev standards and best practices
Conduct research into clients’ use of Salesforce, producing a report of findings with recommended steps and a roadmap for Salesforce solutions.
Lead and advise customers on best practices around data cleansing and transforming raw data using Data workflow leveraging on-platform and off-platform tools, mapping data elements to relevant business representation and partitioning them into the right spaces for business groups to consume in campaigns, automation, and analytics
Develop integration strategies to unify disparate data systems, such as sales, customer service, and marketing, to create a single source of truth across the organization.
Collaborating with data stewards and architects to ensure data quality, consistency, and integrity within the Data Cloud platform.
Implementing AI-powered insights within Salesforce Data Cloud, enabling the organization to utilize artificial intelligence using Salesforce native models for predictive analytics, trend spotting, and decision support.
Ensuring real-time data processing is established, allowing for the immediate updating and availability of data across systems, thereby facilitating timely and informed business decisions.
Customizing data security frameworks to safeguard sensitive information, and setting up rules, and permissions to maintain data integrity and compliance.
Empowering data-driven decision-making by providing stakeholders with access to comprehensive analytics and insights from integrated data sources.
Streamlining operational efficiency through the automation of data-related workflows and the optimization of data access for various business units.
Preparing the organization for AI-readiness by establishing data collection and management practices that will serve as the foundation for future AI applications and innovations.
Designing and refining data ingestion strategies to capture and funnel data into the Data Cloud from a multitude of sources, ensuring accuracy and timeliness.
Developing and applying data transformation logic and formulas to cleanse, restructure, and enrich raw data into meaningful formats.
Creating and managing robust data models that align with the organization’s analytics needs, including the development of custom Data Model Objects (DMOs) when the standard Customer 360 models require augmentation.
Devising mapping strategies for Data Lake Objects (DLOs) to DMOs, ensuring that data flows logically and efficiently within the system.
Establishing best practices for data governance, stewardship, and architecture within the Data Cloud environment to maintain high data quality and compliance standards.
Providing technical leadership in the selection and application of data management tools within the Data Cloud, facilitating the integration of third-party data and leveraging Salesforce’s suite of tools for maximum impact.