Salesforce Data 360 Architect

About the role

A highly experienced Salesforce Data 360 Architect is sought to define and govern end-to-end Salesforce data architecture. The role focuses on designing scalable and secure solutions that unify, govern and activate customer data across the Salesforce ecosystem, combining deep Salesforce Data 360 / Data Cloud expertise with enterprise data architecture, integration, identity resolution and Customer 360 experience.

Key responsibilities

• Define the target-state Salesforce Data 360 architecture and phased implementation roadmap.
• Design data domains, data spaces, environment strategy and non-functional requirements.
• Define ingestion, federation, zero-copy, batch, streaming, API, Change Data Capture and event-driven patterns.
• Develop logical and physical data flows, integration specifications, security models and architecture documentation.
• Design source-to-target mappings from Data Lake Objects (DLOs) to Data Model Objects (DMOs).
• Define transformation, normalization, data quality, lineage, metadata management and reconciliation approaches.
• Architect identity resolution strategies to establish trusted unified customer profiles.
• Design calculated insights, related attributes, segmentation and reusable data products.
• Architect integrations with Salesforce Clouds, MuleSoft, APIs, data warehouses, lakehouses, marketing platforms and enterprise applications.
• Define activation patterns across Sales Cloud, Service Cloud, Marketing Cloud, Commerce, Tableau, Agentforce and approved external platforms.
• Lead architecture and design reviews across multidisciplinary and geographically distributed teams.

Required profile

• Hands-on experience with Salesforce Data 360 / Data Cloud, including data ingestion, harmonization, identity resolution, segmentation and activation.
• Salesforce Data Cloud Consultant certification.
• Strong knowledge of Salesforce data architecture, Customer 360, DLOs/DMOs, APIs and integration patterns.
• Experience with CDP, MDM, data warehouse or lakehouse architectures, including data governance and quality.
• Experience designing scalable solutions for large data volumes, batch and streaming processing.
• Strong enterprise architecture, stakeholder management and cross-functional leadership skills.

Nice to have

• Experience with MuleSoft.
• Experience with Tableau or Agentforce.
• Knowledge of AI grounding patterns, embeddings, vector search and hybrid search.
• Experience integrating Salesforce with enterprise data and analytics platforms.