Overview

As a Forward Deployed Engineer for Data 360, you will implement real-time data capabilities directly in customer environments, turning designs into production data pipelines and AI-grounding layers. You’ll work in a delivery team to connect ingestion, identity, insights, and activation, ensuring secure, scalable deployments. The role combines data engineering with hands-on software engineering to deliver tangible outcomes for enterprise data initiatives. This is a customer-facing, impact-driven position at the intersection of data, AI, and enterprise systems.

Retribuzione / Benefits

- base salary EUR 88,200–117,900 per year
- incentive component tailored by grade level
- accommodations process available
- benefits and resources supporting work-life balance

Responsabilità

- Build in customer sandboxes and production environments using Data 360 configuration, SQL, Apex, Flow, Python, REST API, and deployment tooling
- Engineer the data layer with ingestion, harmonization, and identity resolution for batch and streaming sources
- Validate implementations with representative test data across happy paths, edge cases, and large-scale volumes
- Ground the agents by designing and maintaining the AI data integration layer (RAG, vector databases, knowledge bases)
- Design and implement protocols for agent communication and execution (MCP, agent-to-agent)
- Create scalable, secure data integration patterns connecting Agentforce to enterprise apps
- Govern data governance, security, and privacy across Salesforce ecosystem and external systems
- Build for scale and security with secure authentication/authorization (OAuth, SAML)

and distributed architectures
- Troubleshoot ingestion, mapping, schema drift, and permissions with reproducible results
- Document tradeoffs and hand off implementations to architects orTechnical leads
- Collaborate with customers and partners through reviews, pairing, and handoffs
- Contribute reusable metadata, scripts, tests, and runbooks for repeatable deployments
- Provide input to product roadmap with evidence of platform gaps and edge cases

Requisiti fondamentali

- 8+ years of experience in software or data engineering or technical implementation
- Bachelor's degree in Computer Science or equivalent practical experience
- Hands-on experience with Salesforce Data 360 (Data Cloud) or similar enterprise data platform
- Proficiency in SQL and multi-table query optimization
- Fluency in Apex, Java, Python, or JavaScript/TypeScript; willingness to learn others
- Experience building data pipelines and integrations with current data platforms (e.g., Snowflake, Databricks, BigQuery, Redshift, Kafka)
- Understanding of data modeling, APIs, batch/streaming processing, and data access patterns
- Experience with AI data grounding (vector databases, embedding pipelines, knowledge bases)
- Experience with secure service-to-service integration (OAuth, SAML, event-driven architectures)
- Familiarity with MCP or agent-to-agent protocols is a plus
- Ability to explain built work to customer teams and work in deadline-driven environments
- Relevant Salesforce Agentforce/Data 360 certifications are advantageous

- Customer-focused
- Problem-solving
- Strong collaboration across cross-functional teams
- SQL
- Apex
- Python

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