Salesforce Data Architect

Salesforce Data Architect

Location: Remote

Duration: Long-term Contract

Healthcare domain experience (Huge plus)

US client-facing experience and onsite–offshore coordination (Mandatory)

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/GCP/Snowflake/Databricks familiarity and integration patterns
• Skill 7 – Salesforce Technical Expertise: client/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

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, GCP, 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:

• 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.

Preferred Salesforce.Com Certifications

• Salesforce Certified Data Cloud Consultant (must-have)
• Salesforce Application/System Architect (must have one of the two)

Salesforce Skillset & Knowledge

• Very good experience in having architected and implemented Salesforce solutions, from a Development perspective. Hand-holding Programming team in ensuring client/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.