Data Engineer (SMTS / LMTS, Master Data Management)

• Salesforce is building the most comprehensive understanding of business relationships across our global customer ecosystem. A critical pillar of this effort is Master Data Management (MDM): the systems that identify, enrich, deduplicate, and govern every business entity and corporate hierarchy we interact with
• We are 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
• In these roles, you will design, develop, and operate critical MDM capabilities — including entity resolution, golden record management, corporate hierarchy automation, and enterprise data integration solutions — while leveraging modern AI technologies to build developer tools, engineering automation, and productivity accelerators across the MDM ecosystem
• At the LMTS level, you will drive technical strategy, architect end-to-end platforms, and provide cross-functional leadership. At the SMTS level, you will serve as a hands-on technical leader with a bias for action, translating architecture into scalable, production-grade systems. Both roles partner closely with Product Management, Data Governance, Architecture, Systems Integrator partners, and downstream consuming teams
• 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
• 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, drive root cause analysis, and implement scalable long-term solutions
• Collaborate effectively with globally distributed teams across multiple time zones
• 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 PMTS, Product Owners, TPMs, and business stakeholders to define architecture, roadmap priorities, solution designs, and delivery plans aligned with business objectives
• Provide technical leadership across internal engineering and systems integrator teams

Benefits

• Medical Care
• Life Insurance
• Retirement Savings
• Employee Assistance Programs
• With 9 standard holidays and four floating holidays, you get a total 13 paid days off each year- Proven experience building developer tools using modern AI tech stack like Claude, Cursor etc. in MDM domain
• 10+ years of progressive experience in enterprise integration, data engineering, MDM, or large-scale data platform development
• Excellent communication and collaboration skills
• Strong knowledge of SQL, data modeling, database design, and distributed data processing architectures
• Demonstrated technical leadership, cross-functional collaboration, and ability to drive multiple complex initiatives from design through delivery
• Experience with AWS, GCP, or Azure cloud services and cloud-native application development
• Minimum Qualifications — SMTS (8+ years experience):
• 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
• 8+ years of experience in software engineering, data engineering, enterprise integration, or MDM platforms
• Strong hands-on development experience with Java, REST APIs, microservices, and enterprise integration patterns
• Minimum Qualifications — LMTS (10+ years experience):
• Strong hands-on experience with Informatica SaaS MDM , particularly with party data models including Account, Contact, Organization, and Supplier
• Deep expertise in MDM concepts including entity resolution, golden record lifecycle, match/merge/survivorship, data quality, governance, and hierarchy management
• Experience building MuleSoft integrations, API orchestration services, Airflow workflows, ETL/ELT pipelines, and large-scale data engineering solutions
• A related technical degree required
• Proven experience designing and building API orchestration layers, MuleSoft integrations, microservices, and event-driven architectures
• Excellent communication skills with the ability to influence stakeholders across all levels of the organization
• Experience with Kafka or similar event-streaming technologies, CDC, and event-driven architectures
• 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 (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