S

Salesforce

Builds cloud software for customer relationships

Forward Deployed Engineer - Data 360

Full-Time
No salary listed
Senior
Bachelor's
Düsseldorf, Germany+4 moreMore locations: Frankfurt, Germany | Stuttgart, Germany | Berlin, Germany | Munich, Germany
Remote
Solution EngineeringImplementation & Technical Account Management

About the job

Requirements
  • At least 5 years of experience in software engineering, data engineering, or technical implementation, including a production data solution that can be explained in detail.
  • A bachelor's degree in Computer Science or equivalent practical experience.
  • Hands-on experience implementing Salesforce Data 360 (Data Cloud) or a comparable enterprise data platform across ingestion, modeling, identity, insight, activation, and operations.
  • Hands-on experience building data pipelines and integrations using at least one enterprise data platform or technology, such as Snowflake, Databricks, BigQuery, Redshift, Kafka, cloud object storage, or an enterprise master data management platform.
  • Proficiency in SQL, including building, debugging, and optimizing multi-table queries, joins, filters, transformations, and validation checks.
  • Fluency in at least one enterprise implementation language: Apex, Java, Python, or JavaScript/TypeScript, with willingness to learn the others as needed.
  • Understanding of data modeling, APIs, integration patterns, batch and streaming processing, and the practical differences between copied, federated, and Zero Copy data access.
  • Experience building retrieval systems for AI applications, including vector databases, search indexes, embedding pipelines, or knowledge bases, with the ability to explain chunking, indexing, and relevance decisions.
  • Experience implementing secure service-to-service integration patterns, including OAuth, SAML, and event-driven architectures, and familiarity with MCP and agent-to-agent communication.
  • Ability to implement secure data access and rigorously test permissions, entitlements, consent, user context, restricted populations, and negative test cases.
  • Ability to diagnose technical problems methodically, use logs and query evidence, isolate product behavior from configuration errors, and document reproducible results.
  • Ability to implement against documented architecture, explain implementations to customer technical teams, and recognize when a question requires an architect or security owner.
  • Experience delivering alongside customers, partners, professional services, or internal implementation teams in deadline-driven environments.
  • Ability and willingness to work directly with customer administrators, developers, data engineers, and architects.
Responsibilities
  • Build directly in customer sandboxes and production environments using Data 360 configuration, SQL, Apex, Flow, Python, the REST Query API, the Interaction SDK, Salesforce DX, CLI, Git, Data Kits, and deployment tooling while following security, change-management, and release controls.
  • Build ingestion, harmonization, and identity-resolution processes across batch and streaming sources.
  • Materialize data views optimized for application, analytical, and agentic workloads, tuning latency and cost tradeoffs to meet use-case requirements.
  • Work with customer data and AI teams to align implementations with existing data mesh and data fabric strategies.
  • Create representative test data and validate expected outcomes across normal paths, edge cases, access boundaries, hierarchy behavior, failure conditions, and customer-scale volumes.
  • Design, build, and maintain the AI data integration layer, including retrieval-augmented generation, vector databases, search indexes, and knowledge bases, to ground Agentforce solutions in real-time enterprise data.
  • Design and implement Model Context Protocol and agent-to-agent communication protocols to govern, monitor, and support efficient collaboration among specialized AI agents.
  • Implement scalable and secure data integration patterns connecting Agentforce to enterprise applications and enabling communication between AI agents.
  • Apply data management expertise to securely integrate, transform, and govern structured and unstructured data across the Salesforce ecosystem and external systems.
  • Use message queues, event-driven architecture, and distributed systems to build resilient workflows.
  • Implement secure OAuth and SAML authentication and authorization protocols in accordance with enterprise security policies.
  • Troubleshoot ingestion failures, mapping defects, schema drift, identity anomalies, query behavior, activation latency, API errors, permissions, and consumption issues using logs and query evidence.
  • Compare implementation techniques within approved architectures, document measured tradeoffs, and recommend maintainable implementations to the responsible architect or technical lead.
  • Use AI tooling, including Data 360 APIs and MCP Servers, to automate the build process and reduce customers' time to value.
  • Work alongside customer technical teams and partners through pairing, code reviews, and configuration reviews.
  • Package reusable metadata, scripts, queries, tests, and runbooks so solutions can be reproduced and supported.
  • Support deployment, validation, production handoff, and early stabilization while documenting ownership and known limitations.
  • Surface reproducible platform gaps and edge cases, with live evidence, impact, and expected behavior, to Product and Support.
Desired Qualifications
  • Relevant certifications in Salesforce Agentforce, Data 360, and the Salesforce Platform.

About the company

Salesforce sells cloud software that helps businesses manage sales leads, customer service, marketing, and online commerce from shared customer records. Its flagship Sales Cloud tracks accounts and deals, while Service Cloud organizes support cases and Agentforce builds AI assistants that act on company data. Teams access these tools through a browser and connect outside apps and data sources, with Slack for work messages and Tableau for visual analysis. Salesforce earns most of its revenue from software subscriptions and support, with professional services for implementation and training. Marc Benioff co-founded Salesforce in 1999, and its headquarters are in San Francisco, California.

Company Size

10,001+

Company Stage

IPO

Headquarters

San Francisco, California

Founded

1999

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Simplify Jobs

Simplify's Take

What believers are saying

  • AI brings paying demand: Salesforce reported nearly $3.9 billion in Agentforce and Data 360 recurring revenue pace in August 2026.
  • Giving back gets paid time: Salesforce employees receive seven paid volunteer days each year.
  • Subscriptions provide a durable base: Salesforce earned $10.8 billion from subscriptions and support in the July 2026 quarter.

What critics are saying

  • Office roles demand attendance: Salesforce's published guidelines require four to five days in person for office-based roles.
  • Expansion brought debt: Salesforce borrowed $6 billion in November 2025 to help finance the Informatica acquisition.
  • Reliability failed during Dreamforce: a September 2026 Salesforce outage disrupted affected Hyperforce environments for seven hours and 36 minutes.

What makes Salesforce unique

  • Partners extend its platform: Salesforce's AgentExchange combines third-party apps, AI agents and services with unified purchasing and billing.
  • Everyone publishes a plan: Salesforce employees write annual goals visible to colleagues through its internal V2MOM system.
  • Learning includes real practice: Salesforce's free Trailhead courses award badges after quizzes and hands-on exercises in practice accounts.

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Benefits

Health Insurance

Life Insurance

401(k) Retirement Plan

Remote Work Options

Flexible Work Hours

Parental Leave

Wellness Program

Growth & Insights and Company News

Headcount

6 month growth

-1%

1 year growth

-1%

2 year growth

-2%
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