01 ott - Milano
Salesforce
OverviewAs a Forward Deployed Engineer, you will implement Salesforce Data 360 inside enterprise environments, turning designs into production data solutions.
You work within a delivery team to build ingestion, harmonization, identity, and activation layers, plus AI data integration for Agentforce.
You'll write code in SQL, Apex, Python, and more to deliver real-time, scalable data platforms.
This role blends hands-on data engineering with customer-facing delivery, applying secure, tested solutions at scale.
You'll collaborate across architecture, customers, and partners to drive impactful data-driven outcomes.
Retribuzione / Benefitsincentive component tailored by grade level
accommodations request process
AI-assisted recruitment transparency
ResponsabilitàConfigure and develop in customer sandboxes and production environments using Data 360, SQL, Apex, Flow, Python, REST Query API, Interaction SDK, Salesforce DX, CLI, Git, and deployment tooling
Engineer the data layer across ingestion, harmonization, and identity resolution for batch and streaming sources
Validate implementations with representative test data and check happy paths, edge cases, and scale
Design and implement AI data integration layer (RAG, vector databases, search indexes, knowledge bases) to ground Agentforce solutions
Define protocols for agent collaboration (MCP, agent-to-agent communication) and secure, scalable data integration with enterprise apps
Govern data security, transformation, and governance across Salesforce ecosystem and external systems
Build secure, scalable workflows using messaging queues and event-driven architectures with OAuth/SAML
Diagnose issues with logs, tests,
and data traces; document reproducible results
Lead decisions on architecture tradeoffs and hand off to architects or security owners
Accelerate with AI tooling to automate build processes and reduce time-to-value
Collaborate with customers and partners through reviews, paired programming, and handoffs
Surface platform gaps and edge cases with evidence to Product/Support
Provide deployment, validation, production handoff, and early stabilization with clear ownership
Requisiti fondamentali5+ years in software or data engineering with a production data solution
Bachelor's degree in Computer Science or equivalent practical experience
Hands-on experience with Salesforce Data 360 or similar enterprise data platform
Experience building data pipelines and integrations using platforms like Snowflake, Databricks, BigQuery, Redshift, Kafka, cloud object storage, or MDM
Proficiency in SQL; ability to build and optimize multi-table queries
Fluency in Apex, Java, Python, or JavaScript/TypeScript; willingness to learn others
Understanding of data modeling, APIs, batch/streaming processing, and data access paradigms
Experience building AI retrieval systems (vector DBs, search indexes, embeddings, knowledge bases)
Experience with secure service-to-service integration (OAuth, SAML, event-driven architectures) and agent protocols (MCP)
Ability to implement secure data access, entitlements, consent, and negative testing
Experience delivering with customers, partners, or professional services in deadline-driven environments
Relevant Salesforce certifications in Agentforce, Data 360, and Salesforce Platform
Collaborative
Customer-oriented
Strong problem-solving and methodical debugging
SQL
Apex
Python
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