Description

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

Most technical roles ask you to implement what already exists. This role asks you to define what comes next. You'll work with Data 360 features before they're broadly available, solve data architecture problems before there are playbooks, and build the artifacts that the rest of the field will use for years.

Your Impact

Research & Field Validation

Deploy and stress-test pilot Data 360 features with customers, identifying platform gaps and feeding structured findings back to Technology & Product
Conduct feasibility research on novel data unification, activation, and AI-grounding use cases
Co-develop hypotheses with Technology & Product and design field experiments to validate them
Document and escalate critical engineering issues — including ingestion failures, transform errors, and activation gaps — with detailed evidence packages
Participate in beta testing programs for new Data 360 features (e.g., Data Kits, BDTs, Activation-Triggered Flows)

Customer Engagement

Lead technical engagement of new Data 360 products and features with early adopters
Embed directly with customer teams to architect solutions unifying data across CRM, data lakes (Snowflake, BigQuery, AWS S3), and SaaS platforms
Run rapid prototyping and POC cycles to validate data ingestion, federation, transformation, and activation use cases
Serve as the primary technical advisor and escalation point for your customer portfolio
Support customers in building AI-ready data foundations — unified profiles, vector databases for RAG, consent management, and zero-copy integrations

Product Acceleration & Feedback

Build reusable accelerators, playbooks, and reference architectures that address critical Data 360 product gaps
Raise Voice of Customer (VoC) inputs and influence Salesforce Idea Contributions (SICs) with structured field evidence
Partner directly with Product Managers and Engineers to influence roadmap priorities
Analyze competitive CDP/data platform landscape (Segment, mParticle, Adobe, Informatica) to identify Salesforce's key differentiators
Produce thought leadership, Knowledge Articles, 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 — under real customer conditions
Contribute to hardening agentic Data 360 products for enterprise scale by identifying platform gaps with evidence packages for the Product R&D team
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

5+ years of hands-on experience in enterprise data platforms, SaaS environments, or Salesforce Professional Services
Deep expertise in Salesforce Data 360 — including data ingestion, identity resolution, data model, segmentation, and activation
Strong hands-on experience with Batch Data Transforms (BDTs), calculated insights, and streaming ingestion
Experience designing and implementing zero-copy integrations with external data platforms (Snowflake, BigQuery, AWS)
Proficiency in SQL, data modeling, and ETL/ELT design patterns
Understanding of AI grounding — building vector databases, RAG architectures, and unstructured data pipelines for Agentforce
Experience with Data 360 Activation — segments, activation targets, and triggered flows
Familiarity with data governance, consent management, GDPR/CCPA compliance frameworks within Data 360
Strong diagnostic and problem decomposition instincts
Exceptional written communication skills
Certifications: Salesforce Data 360 Consultant, Salesforce Agentforce Specialist, Platform Developer I
Work Location: Hybrid

Preferred Qualifications

Prior experience in a forward deployed engineering, solutions engineering, or embedded technical advisory role
Experience with multi-cloud delivery — Data 360 + Agentforce + Marketing Cloud
Experience with data integration platforms such as MuleSoft, Informatica, Talend, or AWS Glue
Familiarity with industry-specific data models (Financial Services, Manufacturing, Healthcare, Retail etc.)
High agency, self-motivation, and agility
Platform Developer II certification a plus