AI-Powered Salesforce Data Cloud Architect – Life Sciences

Accenture

New York (NY)

On-site

USD 68,000 - 219,000

Full time

14 days+

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Job summary

Accenture is seeking an early-career Salesforce architect within the Life Sciences Salesforce Business Group. You will build expertise at the intersection of Data Cloud, AI, and commercial transformation for pharma, biotech, and MedTech programs.

You will contribute to architecture and solution design, own discrete technical workstreams, and grow toward independent delivery. You will design data models, support AI-powered workflows, and help integrate Salesforce with external data sources while

Qualifications

Minimum 2 years Salesforce delivery experience in a consulting or SI environment.
Minimum 1 year of Data Cloud experience including data ingestion, identity resolution, segmentation, and activation patterns.
Minimum 1 year of Agentforce hands-on experience or certification with Agentforce, Einstein, or equivalent AI tooling on the Salesforce platform.
CRM fundamentals — solid understanding of Sales Cloud, Service Cloud, Health Cloud, or Life Sciences Cloud.
Minimum 1 year of experience with APIs, data modeling, and integration concepts; experience with REST/SOAP or MuleSoft a plus.
Minimum 1 year of consulting (client-facing) experience.
Bachelor’s degree in Computer Science, Engineering, or equivalent (minimum 12 years) work experience. If Associate’s Degree, must have minimum 6 years work experience.

Responsibilities

Data Cloud architecture — support design and configuration of Data Cloud data models, data streams, identity resolution, and segmentation for Life Sciences use cases
Agentforce & AI build — contribute to implementation of Agentforce agents and AI-powered workflows including Voice AI integrations across patient services and commercial programs
Solution documentation — author and maintain solution design documents, data flow diagrams, and technical specifications across assigned workstreams
Integration support — assist in designing and implementing integrations between Data Cloud, CRM (Salesforce LSC/Health Cloud), and external data sources (EHR, claims, third-party data)
Requirements and workshops — translate client business requirements into user stories, acceptance criteria, and platform configuration decisions; participate in and support facilitation of design workshops
Quality and testing — own technical test scenarios for assigned workstreams; support UAT, performance testing, and go-live readiness activities
Practice contribution — contribute to accelerators, reusable assets, and point-of-view materials for the Life Sciences AI and Data Cloud practice