Salesforce offers an on-site Data Engineer role in San Francisco that blends leadership on master data management with AI powered tooling and cross-functional collaboration. This opportunity supports design, construction, and operation of MDM capabilities such as entity resolution, golden records, and hierarchy automation, while shaping technical strategy and evangelizing AI-assisted engineering practices. The position carries a salary range of USD 148,500 to 285,800 per year and a comprehensive benefits package in addition to a culture focused on innovation, governance, and collaboration.
Benefits
- Time off programs
- Medical
- Dental
- Vision
- Mental health support
- Paid parental leave
- Life and disability insurance
- 401(k)
- Employee stock purchasing program
Responsibilities
- Design, develop, and sustain AI powered developer tools, engineering automation, and productivity accelerators using modern AI platforms such as Claude, Cursor, Windsurf, and GitHub Copilot
- Build and maintain end-to-end MDM integration systems including MuleSoft integrations, Airflow workflows, API orchestration layers, event-driven architectures, Change Data Capture, and batch processing pipelines
- Implement entity resolution, golden record lifecycle management, hierarchy processing, data quality validation, and governance capabilities
- Integrate 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 that support MDM requirements across hierarchical, relational, and party data structures
- Build production-grade solutions with robust monitoring, alerting, operational supportability, and security by design
- Drive adoption of AI assisted software engineering practices to improve developer productivity, testing efficiency, and delivery speed
- Participate in design reviews, code reviews, operational readiness reviews, and release activities
- Troubleshoot complex production issues, perform root cause analysis, and implement scalable long-term solutions
- Collaborate effectively with globally distributed teams across multiple time zones
Responsibilities - 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
- Lead design reviews and establish engineering standards for scalability, observability, resiliency, security, testing, and operational excellence
- Partner with PMs, Product Owners, TPMs, and business stakeholders to define architecture, roadmap priorities, solution designs, and delivery plans aligned with business goals
- Provide technical leadership across internal engineering teams and systems integrator partners
Requirements
- 8+ years of experience in software engineering, data engineering, enterprise integration, or MDM platforms
- 10+ years of progressive experience in enterprise integration, data engineering, MDM, or large-scale data platform development
- Proven experience using modern AI assisted development platforms such as Claude, Cursor, Windsurf, GitHub Copilot, or similar to boost engineering productivity
- Strong understanding of Generative AI and agentic workflows and their practical application in software engineering
- Hands-on experience with Informatica SaaS MDM, especially with party data models including Account, Contact, Organization, and Supplier
- Hands-on development experience with Java, REST APIs, microservices, and enterprise integration patterns
- Experience designing API orchestration layers, MuleSoft integrations, microservices, and event-driven architectures
- Experience with Kafka or similar event-streaming tech, 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 is required
- Deep expertise in MDM concepts including entity resolution, golden record lifecycle, match/merge/survivorship, data quality, governance, and hierarchy management
- Proven experience building developer tools using modern AI tech stacks in the MDM domain
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
- Experience with data stewardship, governance processes, and operational data quality tooling
- Experience with Retrieval-Augmented Generation, vector databases, AI agents, MCP frameworks, or related AI technologies
- Experience building internal developer platforms, engineering productivity tools, or agentic solutions for enterprise teams
- A proven 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
Technologies
- Claude, Cursor, Windsurf, GitHub Copilot
- MuleSoft, Airflow, Kafka
- AWS, GCP, Azure
- Informatica SaaS MDM
- Java, REST APIs, Microservices, Python
- Salesforce Data Cloud
About Salesforce
Salesforce positions itself as a leading AI powered CRM where people and teams drive customer success together. The culture emphasizes ambition, action, trust, and responsible innovation, with an emphasis on practices that support long term impact and values-driven collaboration.
The Experience
Salesforce is building a comprehensive understanding of business relationships across a global ecosystem. A core pillar is Master Data Management, spanning identity, enrichment, deduplication, and governance of business entities and corporate hierarchies. Engineers at SMTS and LMTS levels will design, build, and operate critical MDM capabilities while leveraging modern AI technologies to create developer tools, engineering automation, and productivity enhancements. LMTS roles include technical strategy, platform architecture, and cross-domain leadership.
Accommodations
If you need a reasonable accommodation during the application or recruiting process, please submit a request using the Accommodations Request Form.
Posting Statement
Salesforce is an equal opportunity employer and maintains a policy of non-discrimination. Applications will be evaluated on merit, competence, and fit for the role, with a commitment to inclusive practices and equal opportunity for all applicants.
