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Salesforce Data Cloud Architect

Job in Rosemont, Cook County, Illinois, USA
Listing for: TechDigital Group
Full Time position
Listed on 2026-02-28
Job specializations:
  • IT/Tech
    Data Engineer, Cloud Computing
Salary/Wage Range or Industry Benchmark: 80000 - 100000 USD Yearly USD 80000.00 100000.00 YEAR
Job Description & How to Apply Below
Location: Rosemont

Mandatory Skills-Salesforce Data Cloud, marketing Cloud, Architect

Pre-Requisites:

  • Required minimum of 10+ years of experience in Salesforce Data Cloud and Salesforce Marketing Cloud to collaborate with clients to understand their business objectives and requirements, and design solutions to meet the needs.
  • Architect and design robust and scalable Salesforce Data Cloud solutions based on client requirements and industry best practices.
  • Work with practitioners on Salesforce Marketing Cloud and help build marketing capabilities and assets using data cloud.
  • Understand functional requirements and should be able to develop technical design using standard patterns and be able to communicate the same effectively to the team members.
  • Define and implement data modelling, schema design, and data governance strategies within the Salesforce Data Cloud.
  • Implement seamless integrations between Salesforce Data Cloud and third-party systems, such as marketing automation, analytics, and Salesforce CRM.
  • Collaborate with cross-functional teams to align technical solutions with business objectives.
  • Salesforce certifications in Salesforce Data Cloud/CDP.
Roles and Responsibilities
  • Design and implement scalable data models, build ERD diagrams.
  • Build/configure ingestion, data modeling, segmentation and activation within Salesforce Data Cloud and have an understanding of the various cloud platforms that Salesforce data cloud can integrate specifically with Marketing cloud.
  • Design and implement Data 360 data models, including Data Streams, Data Bundles, Data Lake Objects (DLOs), and Data Model Objects (DMOs).
  • Build and maintain data transformations, including Data Mapper recipes, identity resolution rules, and calculated insights.
  • Create scalable segmentation, activation, and unification pipelines to support personalization and analytics use cases.
  • Optimize data ingestion performance with monitoring, validation, and exception handling processes.
  • Implement real-time and batch data synchronization across enterprise systems and Salesforce clouds.
  • Establish best practices for Data Cloud usage, performance tuning, monitoring, and lifecycle management.
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