Data 360 - Principal Forward Deployed Engineer- Italy
Overview As a Forward Deployed Engineer, you will implement Salesforce Data 360 inside customer environments, turning designs into production-ready data pipelines and AI-ready data layers. You’ll work with cross-functional teams to deliver real-time data foundations that support Agentforce AI agents. The role blends hands-on data engineering and software engineering to solve complex ingestion, identity, and governance challenges at scale. This is an opportunity to help shape how enterprises leverage real-time data and AI in practice.
Retribuzione / Benefits
incentive component tailored by grade level
Responsabilità
Build in customer environments using Data 360, SQL, Apex, Python, Flow and related tooling; deploy from sandbox to production Engineer the data layer: ingestion, harmonization, identity resolution, batch and streaming processing Ground AI agents with RAG, vector databases, search indexes, and knowledge bases Design and implement agent communication protocols (MCP, agent-to-agent) and secure data integration patterns Govern data integration, transformation, and governance across Salesforce ecosystem and external systems Ensure secure authentication/authorization (OAuth, SAML) and compliant enterprise security practices Troubleshoot ingestion, mapping, schema drift, and API issues with reproducible results Collaborate with customers, partners, and internal teams,
delivering handoffs and documentation for ongoing support Contribute to roadmap through feedback and live evidence from deployments
Requisiti fondamentali
8+ years in software or data engineering or technical implementation with a production data solution Bachelor’s degree in Computer Science or equivalent practical experience Hands-on experience implementing Salesforce Data 360 or similar data platform across ingestion, modeling, identity, insight, activation, and operations Experience building data pipelines and integrations with enterprise data platforms (e.g., Snowflake, Databricks, BigQuery, Redshift, Kafka) Proficiency in SQL; ability to write and optimize multi-table queries Fluency in at least one enterprise language (Apex, Java, Python, or JavaScript/TypeScript) and willingness to learn others Understanding of data modeling, APIs, integration patterns, and batch/streaming processing Experience building AI retrieval/app knowledge systems (vector databases, indexing, embeddings) Experience with secure service-to-service integration (OAuth, SAML) and agent protocols (MCP) Ability to implement against documented architecture and communicate with customer technical teams Experience delivering with customers/partners in deadline-driven environments Relevant Salesforce Agentforce/Data 360 certifications (preferred) Customer-facing collaboration Methodical problem-solving Clear communication with technical and non-technical stakeholders Data 360 (Data Cloud) experience SQL Apex
Retribuzione / Benefits
incentive component tailored by grade level
Responsabilità
Build in customer environments using Data 360, SQL, Apex, Python, Flow and related tooling; deploy from sandbox to production Engineer the data layer: ingestion, harmonization, identity resolution, batch and streaming processing Ground AI agents with RAG, vector databases, search indexes, and knowledge bases Design and implement agent communication protocols (MCP, agent-to-agent) and secure data integration patterns Govern data integration, transformation, and governance across Salesforce ecosystem and external systems Ensure secure authentication/authorization (OAuth, SAML) and compliant enterprise security practices Troubleshoot ingestion, mapping, schema drift, and API issues with reproducible results Collaborate with customers, partners, and internal teams,
delivering handoffs and documentation for ongoing support Contribute to roadmap through feedback and live evidence from deployments
Requisiti fondamentali
8+ years in software or data engineering or technical implementation with a production data solution Bachelor’s degree in Computer Science or equivalent practical experience Hands-on experience implementing Salesforce Data 360 or similar data platform across ingestion, modeling, identity, insight, activation, and operations Experience building data pipelines and integrations with enterprise data platforms (e.g., Snowflake, Databricks, BigQuery, Redshift, Kafka) Proficiency in SQL; ability to write and optimize multi-table queries Fluency in at least one enterprise language (Apex, Java, Python, or JavaScript/TypeScript) and willingness to learn others Understanding of data modeling, APIs, integration patterns, and batch/streaming processing Experience building AI retrieval/app knowledge systems (vector databases, indexing, embeddings) Experience with secure service-to-service integration (OAuth, SAML) and agent protocols (MCP) Ability to implement against documented architecture and communicate with customer technical teams Experience delivering with customers/partners in deadline-driven environments Relevant Salesforce Agentforce/Data 360 certifications (preferred) Customer-facing collaboration Methodical problem-solving Clear communication with technical and non-technical stakeholders Data 360 (Data Cloud) experience SQL Apex