Salesforce Data Cloud Architect

Role: Salesforce Data Cloud Architect 

Location: Atlanta, GA (3 days a week onsite)

Duration: 12+ Months

Must Have –

• Need Cloud Architect
• Data cloud
• Security
• warehouse concept
• ETL concept
• any cloud
• Healthcare- good to have
• offshore/ onshore coordination

Must Have:

Salesforce Data Cloud (3+ years hands-on): Data models, harmonization, identity resolution, calculated insights, DLOs, segmentation, DQL

Data Cloud Architecture & Customer 360: CDP, unified data platforms, real-time personalization, predictive insights

Agentforce + AI/ML Integrations: Einstein Studio, Model Builder, RAG retrievers, external LLM integrations

Data Architecture & Governance: MDM, data security, compliance, data modeling, data lake/warehouse concepts

Data Integrations: API-based integrations, ETL/ELT pipelines, MuleSoft, event-driven designs

Cloud-native Platforms: AWS/Azure/Google Cloud Platform/Snowflake/Databricks familiarity and integration patterns

Salesforce Technical Expertise: Apex/Visualforce/Lightning, Salesforce API frameworks, Marketing Cloud, MuleSoft, Tableau

Enterprise Architecture Alignment: Ability to engage EA teams for Salesforce data models and scalable architecture decisions

Healthcare domain experience (Huge plus but not mandatory)

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)

Requirements:

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.

Proven track record in designing and implementing data architectures within the Salesforce ecosystem.

In-depth knowledge of Salesforce Data Cloud (Customer 360) and related technologies (MuleSoft, Marketing Cloud, Tableau, etc.).

Strong understanding of Salesforce architecture, including integration patterns, data modeling, and API frameworks.

Hands-on experience with Salesforce data tools like Salesforce Data Loader, Einstein Analytics, and other data management platforms.

Data Management:

Expertise in data governance, data security, and regulatory compliance.

Strong experience with data integration, ETL (Extract, Transform, Load) processes, and middleware platforms like MuleSoft.

Experience in working with client in USA is a Must, and in coordinating between Onsite-Offshore daily

Healthcare domain experience is a huge plus.

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

Data Cloud Strategy & Architecture: Design the overall data architecture strategy for Salesforce Data Cloud, ensuring alignment with business objectives and Salesforce best practices.

Data Integration: Architect and implement integration solutions between Salesforce Data Cloud and other enterprise systems, ensuring data consistency and integrity across platforms.

Data Governance: Establish and enforce data governance practices, ensuring data accuracy, quality, security, and compliance with relevant regulations (e.g., GDPR, CCPA).

Data Modeling: Define data models and structures within Salesforce Data Cloud to support business processes and reporting requirements. Design scalable and maintainable data architectures.

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.

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

Strong Problem-solving skills, with ability to get multiple solutions for/approaches to solve a problem/scenario

Thanks

Yashasvi Hasija

Senior Technical Recruiter | Empower Professionals

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   | Phone:  x 368 | Fax:

LinkedIn: linkedin.com/in/yashasvi-hasija-6a745625b

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