Salesforce Consultant, Data 360

Role Overview

• Research & Field Validation
• Support deployment and stress-testing of pilot Data 360 features with customers, identifying platform gaps and feeding structured findings back to Technology & Product
• Assist in feasibility research on novel data unification, activation, and AI-grounding use cases
• Help co-develop hypotheses with Technology & Product teams and support field experiments
• Document engineering observations, ingestion failures, transform errors, and activation gaps with structured evidence
• Participate in beta testing programs for new Data 360 features
• Customer Engagement
• Support technical engagement of new Data 360 products and features alongside senior FDE team members
• Assist in embedding with customer teams to understand their data estate and contribute to solution architecture
• Participate in rapid prototyping and POC cycles to validate technical feasibility
• Build foundational skills as a technical contributor and junior escalation support
• Support customers in building AI-ready data foundations — unified profiles, consent management, and zero-copy integrations
• Product Acceleration & Feedback
• Contribute to building reusable accelerators, playbooks, and reference architectures that address Data 360 product gaps
• Support senior FDEs in capturing and documenting Voice of Customer (VoC) inputs and SICs with structured field evidence
• Help produce Knowledge Articles, best practices, and enablement content
• Field R&D Engagement
• Support the qualifying R&D activities for the Data 360 FDE program
• Provide structured access to customer data schemas, DLO/DMO designs, and agent configurations to inform future Data 360 product design improvements
• Support feasibility prototyping of emerging Data 360 capabilities
• Contribute to hardening agentic Data 360 products for enterprise scale by identifying platform gaps with evidence packages
• Assist in codifying accelerators, playbooks, and reference architectures to enable scale across Services & Partners
• Participate in beta and pilot programs for incubation-stage Data 360 products selected by Product GMs

Requirements

• 2–3 years of hands-on experience in enterprise data platforms, SaaS environments, or Salesforce Professional Services
• Working knowledge of Salesforce Data 360 — including data ingestion, data model, segmentation, and activation concepts
• Foundational experience with Batch Data Transforms (BDTs), calculated insights, or streaming ingestion
• Proficiency in SQL and comfort with data modeling and ETL/ELT concepts
• Basic understanding of zero-copy integrations or external data platforms (Snowflake, BigQuery, AWS)
• Awareness of AI grounding concepts — RAG, vector databases, and unstructured data pipelines for Agentforce
• Familiarity with Data 360 Activation — segments, activation targets, and triggered flows
• Exposure to data governance and consent management frameworks within Data 360
• Awareness of Salesforce's R&D qualification framework for FDE engagements — understanding the distinction between standard delivery and qualifying R&D activities
• Ability to document structured field observations — customer data schemas, DLO configurations, agent designs — in a form actionable by Product & Engineering teams
• Familiarity with Data 360 Spring '26 features — including Enhanced Retriever Pre-Filters, Notebook AI, Data Kit deployments by Data Space, and Dynamic Retriever Filters
• Solid written communication skills
• Certifications: Salesforce Data 360 Consultant (or actively pursuing), Salesforce Agentforce Specialist

Tech Stack

• AWS
• BigQuery
• ETL
• Spring
• SQL

Benefits

• Health insurance
• 401(k) matching
• Flexible working hours
• Paid time off
• Professional development opportunities