Data Engineer (SMTS / LMTS) - MDM

Job Overview Senior Member of Technical Staff (SMTS) / Lead Member of Technical Staff (LMTS) – Master Data Management (MDM) Engineering, Salesforce. 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. 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 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. Additional Responsibilities for 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 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. Minimum Qualifications – SMTS (8+ years) 8+ years of experience in software engineering, data engineering, enterprise integration, or MDM platforms. Proven experience leveraging modern AI‑assisted development platforms to improve engineering productivity. Strong understanding of generative AI and agentic workflows and their practical application within software engineering organizations. Hands‑on experience with Informatica SaaS MDM, especially party data models (Account, Contact, Organization, Supplier). 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. Related technical degree required. Minimum Qualifications – LMTS (10+ years) 10+ years of progressive experience in enterprise integration, data engineering, MDM, or large‑scale data platform development. Deep expertise in MDM concepts including entity resolution, golden record lifecycle, match/merge/survivorship, data quality, governance, and hierarchy management. Proven experience designing and building API orchestration layers, MuleSoft integrations, microservices, and event‑driven architectures. Proven experience building developer tools using modern AI tech stack like Claude, Cursor, etc. in the MDM domain. Demonstrated technical leadership, cross‑functional collaboration, and ability to drive multiple complex initiatives from design through delivery. Excellent communication skills with the ability to influence stakeholders across all levels of the organization. Related technical degree required. Desired Additional Experience 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. Benefits Salesforce offers a comprehensive benefits package including time‑off, medical, dental, vision, mental health support, paid parental leave, life and disability insurance, 401(k), employee stock purchase, and equity opportunities. Base salary for this position ranges from $148,500 to $260,100, with higher ranges for select metros. Legal Discrimination Statement Salesforce is an equal‑opportunity employer. All employment decisions are made on the basis of merit, competence, and qualifications without regard to race, religion, color, national origin, sex, sexual orientation, gender identity or expression, disability, veteran status, or any other protected class, in compliance with applicable law. #J-18808-Ljbffr Centaur Labs