Associate Principal - Architecture

Job Description Salesforce Data 360 Data Cloud Solution Architect

Role Salesforce Data 360 Data Cloud Solution Architect

Experience 10 years overall Salesforce enterprise data experience with strong handson Salesforce Data Cloud Data 360 architecture and implementation experience

Role Summary

We are seeking an experienced Salesforce Data 360 Data Cloud Solution Architect to augment the enterprise platform team and provide architecture leadership for establishing and evolving the Data 360 foundation

The architect will work alongside the existing Salesforce Professional Services initiative and ensure that the solution designed for the initial business use case evolves into an enterprisescale reusable secure and extensible data foundation The platform is expected to enable future Salesforce Marketing Cloud Next analytics personalization automation and Agentic AI use cases

Key Roles Responsibilities

1 Data 360 Architecture Strategy

Define the overall Salesforce Data 360 Data Cloud architecture principles standards and implementation roadmap

Assess the current Salesforce and enterprise data landscape and establish the targetstate Data 360 architecture

Ensure that the architecture developed for the initial use case can scale to additional business units customer journeys geographies Salesforce clouds and AI use cases

Establish architectural patterns covering ingestion harmonization identity segmentation activation analytics and AI consumption

Maintain alignment between immediate delivery priorities and longerterm enterprise platform objectives

2 Enterprise Data Foundation

Design the enterprise data model using appropriate Data Model Objects DMOs standard objects custom objects and relationships

Define reusable data domains and canonical patterns for customer account contact product transaction engagement service and digital interaction data

Create standards for Data Streams Data Lake Objects DLOs DMOs calculated insights and activation targets

Avoid pointsolution architecture that creates technical debt or limits future use cases

Define data retention lifecycle archival scalability and consumption principles

3 Data Integration Ingestion

Architect ingestion of data from Salesforce and enterprise platforms including appropriate use of

oSalesforce CRM

oMarketing platforms

oERP systems such as SAP

oData warehouseslakes

oAPIs and middleware such as MuleSoft

oBatch and streaming sources

Determine appropriate ingestion patterns and latency requirements for batch nearrealtime and streaming integration

Define error handling reconciliation observability and dataquality controls

Work with integration and sourcesystem teams to resolve dataquality and datacontract issues

4 Identity Resolution Customer 360

Develop the enterprise strategy for customer identity and profile unification

Configure and govern identity resolution matching reconciliation and survivorship rules

Determine appropriate identifiers and match keys across Salesforce and nonSalesforce systems

Prevent incorrect profile merging and excessive profile fragmentation

Define processes for monitoring and continuously improving identityresolution quality

Establish a trusted Customer 360 profile capable of supporting downstream CRM marketing analytics and AI use cases

5 SFMCMarketing Cloud Next Activation

A key part of the requirement is the combination of Data 360 expertise with an understanding of SFMCMarketing Cloud Next

Responsibilities include

Define how unified customer information will be consumed by SFMCMarketing Cloud Next

Design segmentation and audience activation architecture

Support personalized customer journeys and nextbestaction scenarios

Establish reusable calculated insights and audience definitions

Define activation patterns across Salesforce and external channels

Ensure consent and communication preferences are incorporated into audience activation

6 Agentic AI Agentforce Enablement

The Data 360 foundation is specifically expected to become a catalyst for broader Agentic AI and Salesforce use cases

The architect should therefore

Design Data 360 so trusted enterprise data can be safely consumed by Salesforce AI capabilities

Identify reusable customer context and data products suitable for AIAgentforce scenarios

Define grounding patterns for AI use cases using unified enterprise information

Work with AI and Salesforce architecture teams to identify data readiness gaps

Establish appropriate controls for privacy permissions data quality and sensitive information used by AI

Support future use cases such as serviceagent assistance personalized recommendations sales intelligence and automated customer interactions

7 Security Privacy Governance

Define Salesforce Data 360 accesscontrol and security architecture

Establish sta