Position: Salesforce Data Cloud Architect
Remote
Long Term
Must Have Skills
Skill 1 Salesforce Data Cloud (3+ years hands-on): Data models, harmonization, identity resolution, calculated insights, DLOs, segmentation, DQL
Skill 2 Data Cloud Architecture & Customer 360: CDP, unified data platforms, real-time personalization, predictive insights
Skill 3 Agentforce + AI/ML Integrations: Einstein Studio, Model Builder, RAG retrievers, external LLM integrations
Skill 4 Data Architecture & Governance: MDM, data security, compliance, data modeling, data lake/warehouse concepts
Skill 5 Data Integrations: API-based integrations, ETL/ELT pipelines, MuleSoft, event-driven designs
Skill 6 Cloud-native Platforms: AWS/Azure/Google Cloud Platform/Snowflake/Databricks familiarity and integration patterns
Skill 7 Salesforce Technical Expertise: Apex/Visualforce/Lightning, Salesforce API frameworks, Marketing Cloud, MuleSoft, Tableau
Skill 8 Enterprise Architecture Alignment: Ability to engage EA teams for Salesforce data models and scalable architecture decisions
Domain Experience
Healthcare domain experience (Huge plus)
US client-facing experience and onsite offshore coordination (Mandatory)
Must Have Certifications
Salesforce Certified Data Cloud Consultant (Mandatory)
Salesforce Application Architect or Salesforce System Architect (At least one mandatory)
OVERALL EXPERIENCE
8 10+ years in Salesforce/enterprise data platforms, with 3+ years hands-on experience in Salesforce Data Cloud.
Deep understanding of Data Cloud architecture, objects, data models, data lake objects, harmonization, calculated insights, and identity resolution.
Expertise in Data Cloud Query Language (DQL) and advanced segmentation strategies.
Strong knowledge of data architecture, data governance, MDM, data lakes and data warehousing concepts.
Hands-on experience designing large-scale CDP and unified data platforms.
Familiarity and experience working with cloud-native architectures (AWS, Azure, Google Cloud Platform, Snowflake, Databricks).
Expertise in API-based integrations, ETL/ELT pipelines, and event-driven architectures.
Must have proven experience in architecting Agentforce solutions with AI/ML integrations with Data Cloud, including Einstein Studio and RAG-based retrievers.
Experience working with model builder and integrating external LLMs with Agentforce
Strong grounding in real-time personalization, predictive insights, and recommendation engines.
Technical Expertise:
o Proven track record in designing and implementing data architectures within the Salesforce ecosystem.
o In-depth knowledge of Salesforce Data Cloud (Customer 360) and related technologies (MuleSoft, Marketing Cloud, Tableau, etc.).
o Strong understanding of Salesforce architecture, including integration patterns, data modeling, and API frameworks.
o Hands-on experience with Salesforce data tools like Salesforce Data Loader, Einstein Analytics, and other data management platforms.
Data Management:
o Expertise in data governance, data security, and regulatory compliance.
o Strong experience with data integration, ETL (Extract, Transform, Load) processes, and middleware platforms like MuleSoft.
SALESFORCE SKILLSET & KNOWLEDGE
Very good experience in having architected and implemented Salesforce solutions, from a Development perspective. Hand-holding Programming team in ensuring Apex/Visualforce/Lightning based solutions are implemented correctly and efficiently.
Must have Data Cloud Skills and Knowledge
o Data Cloud Strategy & Architecture: Design the overall data architecture strategy for Salesforce Data Cloud, ensuring alignment with business objectives and Salesforce best practices.
o Data Integration: Architect and implement integration solutions between Salesforce Data Cloud and other enterprise systems, ensuring data consistency and integrity across platforms.
o Data Governance: Establish and enforce data governance practices, ensuring data accuracy, quality, security, and compliance with relevant regulations (e.g., GDPR, CCPA).
o Data Modeling: Define data models and structures within Salesforce Data Cloud to support business processes and reporting requirements. Design scalable and maintainable data architectures.
o Customer 360 Solutions: Lead the implementation of Salesforce Data Cloud to enable a single view of customers (Customer 360), ensuring optimal customer insights and analytics for personalized customer engagement.
o Advanced Analytics & AI: Collaborate with teams to integrate AI-driven analytics and predictive models within Salesforce, leveraging data cloud insights to drive business outcomes.
Must be able to engage with Enterprise Architecture teams in discussing Salesforce Data Modeling
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