Data Engineer (SMTS / LMTS) - MDM

About the role

Salesforce is seeking talented engineers at the Senior Member of Technical Staff (SMTS) and Lead Member of Technical Staff (LMTS) levels to join our MDM Engineering organization. The ideal candidate will design, develop, and operate critical MDM capabilities while leveraging modern AI technologies.

Responsibilities

• 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
• 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
• Implement entity resolution, golden record lifecycle management, hierarchy processing, data quality validation, and governance capabilities
• 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
• Design and optimize data models, database schemas, APIs, and integration patterns supporting MDM business requirements across hierarchical, relational, and party data structures
• Build production-grade solutions with strong monitoring, alerting, operational supportability, and security by design
• Troubleshoot complex production issues, drive root cause analysis, and implement scalable long-term solutions
• Collaborate effectively with globally distributed teams across multiple time zones
• LMTS: Architect and evolve end-to-end MDM integration systems and define technical strategy for entity resolution, golden record lifecycle, hierarchy management, data quality, and governance across multiple business domains
• LMTS: Lead design reviews and establish engineering standards for scalability, observability, resiliency, security, testing, and operational excellence
• LMTS: Partner with PMTS, Product Owners, TPMs, and business stakeholders to define architecture, roadmap priorities, solution designs, and delivery plans aligned with business objectives

Requirements

• SMTS (8+ years experience): 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
• 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

Qualifications

• Related technical degree required
• Even Better If:
• Experience with Salesforce Data Cloud, CRM platforms, or broader Salesforce ecosystem technologies
• Experience working with corporate hierarchy data from Dun & Bradstreet, Moody's, or Leadspace, including family tree traversal, DUNS resolution, monitoring, and registration workflows
• Experience building Python-based data engineering frameworks and automation solutions
• Knowledge of data stewardship, governance processes, and operational data quality tooling
• Experience with Retrieval-Augmented Generation (RAG), vector databases, AI agents, MCP frameworks, or related AI technologies
• Experience building internal developer platforms, engineering productivity tools, or agentic solutions supporting enterprise engineering teams
• Demonstrated track record of driving measurable engineering productivity improvements through AI-enabled tooling and automation
• Certifications in MDM, data management, cloud platforms, MuleSoft, Informatica, or related technologies

Skills

• Generative AI and agentic workflows
• Informatica SaaS MDM
• Java, REST APIs, microservices, and enterprise integration patterns
• MuleSoft integrations, API orchestration services, Airflow workflows, ETL/ELT pipelines, and large-scale data engineering solutions
• Kafka or similar event-streaming technologies, CDC, and event-driven architectures
• AWS, GCP, or Azure cloud services
• SQL, data modeling, database design, and distributed data processing architectures
• Python-based data engineering frameworks and automation solutions
• Data stewardship, governance processes, and operational data quality tooling
• Retrieval-Augmented Generation (RAG), vector databases, AI agents, MCP frameworks, or related AI technologies
• Internal developer platforms, engineering productivity tools, or agentic solutions supporting enterprise engineering teams

Benefits

At Salesforce, we offer a variety of benefits to help you live well including: time off programs, medical, dental, vision, mental health support, paid parental leave, life and disability insurance, 401(k), and an employee stock purchasing program. For more details, visit this link.

Pay

The typical base salary range for this position is $148,500 - $260,100 annually. In select cities within the San Francisco and New York City metropolitan area, the base salary range for this role is $178,900 - $285,800 annually. The range represents base salary only, and does not include company bonus, incentive for sales roles, equity or benefits, as applicable.

Schedule

Flexible work arrangements are available to support your needs.