Salesforce Data Cloud Architect

4 days ago


Detroit, United States Tech Mahindra Full time

Responsibilities:

• Design and implement data solutions using Salesforce Data Cloud to manage and integrate customer data across various systems.

• Design and configure data models, including data extensions, data imports, and data transformations within Salesforce Data Cloud.

• Manage custom data pipelines, workflows, and automation to streamline data processes and enhance data quality.

• Collaborate with stakeholders to gather data requirements and translate them into technical solutions using Salesforce Data Cloud.

• Utilize Salesforce Data Cloud’s capabilities for customer segmentation, audience management, and personalized marketing strategies.

• Monitor data integration processes, troubleshoot issues, and ensure data accuracy and consistency across platforms.

• Create and manage dashboards and reports to provide insights into data performance and usage.

• Ensure compliance with data governance, security policies, and industry regulations.

Requirements:

• Bachelor’s degree in Computer Science, Data Science, Information Technology, or a related field.

• Proven experience working with Salesforce Data Cloud or similar data management platforms.

• Strong knowledge of Salesforce Data Cloud features and functionalities, including data modeling, integration, and analytics.

• Proficiency in Salesforce development tools, such as Apex, SOQL, and Salesforce Data Loader.

• Experience with data integration tools and techniques (e.g., ETL processes, APIs).

• Familiarity with data visualization and reporting tools within the Salesforce ecosystem.

• Strong problem-solving skills and attention to detail.

• Excellent communication and teamwork skills.

• Preferred Qualifications:

Data cloud certification is mandatory.

Salesforce certifications, such as Salesforce Data Architect or Salesforce Administrator.

Experience with Salesforce Marketing Cloud or Salesforce Service Cloud.

Knowledge of additional programming languages or data manipulation tools (e.g., Python, SQL).

This description may vary depending on the organization and the specific needs of the role.



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