Data Engineer (smts / Lmts) - Mdm

Salesforce Salesforce · Enterprise · San Francisco, CA +3

Salesforce is seeking Senior/Lead Data Engineers to join their MDM Engineering organization. The role involves designing, developing, and operating Master Data Management (MDM) capabilities, including entity resolution and data integration. A key aspect is leveraging modern AI technologies and AI-assisted development platforms to build developer tools, engineering automation, and productivity accelerators within the MDM ecosystem. The role also involves building and maintaining integration systems, implementing MDM functionalities, and collaborating with various teams.

What you'd actually do

  1. Design, develop, and maintain AI-powered developer tools, engineering automation, and productivity accelerators using modern AI platforms such as Claude, Cursor, Windsurf, GitHub Copilot, and related technologies
  2. Build and maintain end-to-end MDM integration systems, including MuleSoft integrations, Airflow-based workflows, API orchestration layers, event-driven architectures, Change Data Capture (CDC), and batch processing pipelines
  3. Implement entity resolution, golden record lifecycle management, hierarchy processing, data quality validation, and governance capabilities
  4. Build and maintain integrations with third-party data providers such as Dun & Bradstreet, Moody's, and Leadspace to support data enrichment and corporate hierarchy management
  5. Design and optimize data models, database schemas, APIs, and integration patterns supporting MDM business requirements across hierarchical, relational, and party data structures

Skills

Required

  • 8+ years of experience in software engineering, data engineering, enterprise integration, or MDM platforms
  • Proven experience leveraging modern AI-assisted development platforms (Claude, Cursor, Windsurf, GitHub Copilot, or similar) to improve engineering productivity
  • Strong understanding of Generative AI and agentic workflows and their practical application within software engineering organizations
  • Strong hands-on experience with Informatica SaaS MDM , particularly with party data models including Account, Contact, Organization, and Supplier
  • Strong hands-on development experience with Java, REST APIs, microservices, and enterprise integration patterns
  • Experience building MuleSoft integrations, API orchestration services, Airflow workflows, ETL/ELT pipelines, and large-scale data engineering solutions
  • Experience with Kafka or similar event-streaming technologies, CDC, and event-driven architectures
  • Experience with AWS, GCP, or Azure cloud services and cloud-native application development
  • Strong knowledge of SQL, data modeling, database design, and distributed data processing architectures
  • Excellent communication and collaboration skills
  • A related technical degree required

What the JD emphasized

  • Proven experience leveraging modern AI-assisted development platforms (Claude, Cursor, Windsurf, GitHub Copilot, or similar) to improve engineering productivity
  • Strong understanding of Generative AI and agentic workflows and their practical application within software engineering organizations
  • Strong hands-on experience with Informatica SaaS MDM , particularly with party data models including Account, Contact, Organization, and Supplier

Other signals

  • AI-powered developer tools
  • engineering automation
  • productivity accelerators
  • modern AI platforms
  • agentic workflows