Description

Design and implement scalable Salesforce Data Cloud architectures for unified customer data and real-time personalization.

Responsibilities

• Architect and maintain Salesforce Data Cloud environments, including data models, harmonization, identity resolution, and segmentation.
• Design and deploy Agentforce solutions with AI/ML integrations, leveraging Einstein Studio, Model Builder, and RAG retrievers.
• Develop API-based integrations, ETL/ELT pipelines, and event-driven architectures using MuleSoft and cloud-native platforms.
• Define data governance, security, and compliance standards for large-scale CDP and unified data platforms.
• Collaborate with Enterprise Architecture teams to align Salesforce data models with scalable enterprise decisions.

Required Skills

• 8+ years in Salesforce or enterprise data platforms, with 3+ years hands-on experience in Salesforce Data Cloud.
• Deep expertise in Data Cloud architecture, objects, data lake objects (DLOs), calculated insights, and Identity Resolution.
• Proficiency in Data Cloud Query Language (DQL) and advanced segmentation strategies.
• Experience designing large-scale CDPs with real-time personalization and predictive insights.
• Strong knowledge of data architecture, MDM, data lakes, and data warehousing concepts.
• Familiarity with cloud-native architectures (AWS, Azure, GCP, Snowflake, Databricks) and integration patterns.
• Hands-on experience with API frameworks, ETL/ELT processes, and middleware like MuleSoft.
• Proven experience architecting Agentforce solutions with external LLM integrations.
• Salesforce Certified Data Cloud Consultant and Salesforce Application/System Architect certifications.

Key Skills

Education

Any Graduate