Description

About the Role

The Product Forward Deployed Engineering (FDE) team is Salesforce's zero-to-one engine for new agentic product innovation. As a Data 360 FDE Associate, you will embed directly with our most strategic customers to validate emerging Data 360 capabilities, support platform hardening under real-world conditions, and help transform every field insight into repeatable patterns that shape the product roadmap.

The ideal candidate is curious, eager to learn, and energized by ambiguity. You don't need to have all the answers — but you bring rigour, a bias for action, and a genuine passion for data platforms and AI.

Your Impact

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 (e.g., Data Kits, BDTs, Activation-Triggered Flows, zero-copy integrations)

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 — including product gap analysis, experimental use case feasibility, feasibility prototyping, and non-production R&D activities
• 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 — including Data Kits, Batch Data Transforms, Dynamic Retriever Filters, and Notebook AI
• 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

Required Qualifications

• 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
• Work Location: Hybrid

Preferred Qualifications

• Exposure to multi-cloud delivery — Data 360 + Agentforce + Marketing Cloud + MuleSoft integration patterns
• Basic proficiency in Python or JavaScript for data scripting and automation
• Familiarity with data integration platforms such as MuleSoft, Informatica, or AWS Glue
• Exposure to industry-specific data models (Financial Services, Manufacturing, Healthcare, Retail)
• Experience supporting customer-facing technical engagements — presales, delivery, or embedded advisory roles
• Prior exposure to FDE Momentum Program engagements or product incubation pilot programs
• Experience contributing to VoC or SIC processes with structured evidence
• Familiarity with Data 360 Agents — including Agentic Data Cloud pilots, Data Q&A, and Real-Time Data Graphs
• Understanding of the product-led FDE model — operating as a field R&D engineer focused on product hardening, adoption acceleration, and attrition protection
• A growth mindset — you thrive in ambiguous environments, learn fast, and default to curiosity and experimentation
• Platform Developer I certification a plus