Data Engineer (SMTS / LMTS, Master Data Management)

Join Salesforce as a Data Engineer in the Master Data Management (MDM) Engineering organization. In this role, you will design, develop, and operate critical MDM capabilities, leveraging modern AI technologies. You will have the opportunity to drive technical strategy, architect end-to-end platforms, and provide cross-functional leadership. This position offers a competitive salary, comprehensive benefits, and the chance to work with a global team.

- Design, develop, and operate critical Master Data Management (MDM) capabilities, including entity resolution, golden record management, and corporate hierarchy automation. - Drive technical strategy, architect end-to-end platforms, and provide cross-functional leadership at the Lead Member of Technical Staff (LMTS) level. - Build and maintain end-to-end MDM integration systems, including MuleSoft integrations, Airflow-based workflows, API orchestration layers, and event-driven architectures.

- 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