Enterprise Data Architect — AI & Cloud Solutions

Salesforce, Inc.; New York (NY); On-site; USD 218,000 - 365,000; Full time

Job summary

Salesforce, Inc. is seeking a Data Solutions Architect with deep experience in enterprise data platforms to design reference implementations across Data 360, Tableau, MuleSoft, Slack, Agentforce, and Marketing Cloud Next on the Salesforce platform.

You will tackle production challenges, build governed data products, and mentor engineers while aligning with security and governance standards to deliver analytics-ready data for AI agents.

Qualifications

• Several years delivering complex enterprise implementations on Data 360 and the Salesforce platform in production.
• Working knowledge of at least two of Tableau, MuleSoft, Agentforce, Slack and Marketing Cloud Next.
• Strong grounding in data architecture, security, governance and cloud data platforms such as Snowflake.
• Hands-on skill with APIs, infrastructure-as-code and testing, and the credibility to advise senior leaders.

Responsibilities

• Design and build reference implementations across Data 360, Tableau, Agentforce, MuleSoft, Slack, Marketing Cloud Next and the core Salesforce platform
• Solve production challenges: identity, access control, consent, governance, multi-region deployment and reliability
• Build governed data products and semantic models for analytics and AI agents, and compare Salesforce with alternatives such as Snowflake based on tested requirements
• Document decisions and reusable patterns, and mentor architects and engineers

Skills

Data 360

Salesforce Platform

APIs

Infrastructure as Code

Governance

Tools

Tableau

MuleSoft

Agentforce

Slack

Marketing Cloud Next

Snowflake

Job description

Salesforce, Inc. is seeking a Data Solutions Architect with deep experience in enterprise data platforms to design reference implementations across Data 360, Tableau, MuleSoft, Slack, Agentforce, and Marketing Cloud Next on the Salesforce platform.

You will tackle production challenges, build governed data products, and mentor engineers while aligning with security and governance standards to deliver analytics-ready data for AI agents.