Principal Data Engineer – MDM

Salesforce

Principal Data Engineer at Salesforce leading technical vision for Enterprise Knowledge Graph platforms. Collaborating closely with AI, architecture, and data engineering teams to drive innovations.

Posted 6/20/2026full-timeSan Francisco • California, New York, Washington • 🇺🇸 United StatesLead💰 $197,300 - $313,700 per yearWebsite

Tech Stack

Tools & technologies

AWSAzureCloudDistributed SystemsGoogle Cloud PlatformMicroservicesNeo4j

About the role

Key responsibilities & impact

Define and drive the long-term technical vision, architecture, and roadmap for Salesforce's Enterprise Knowledge Graph platform.
Lead architecture and design for knowledge graph ecosystems, including graph data models, ontologies, semantic layers, entity resolution frameworks, graph APIs, vector search capabilities, and retrieval architectures supporting AI and agentic use cases.
Establish enterprise standards, governance models, engineering patterns, and best practices for Knowledge Graph development, deployment, and lifecycle management.
Define strategies for integrating structured, unstructured, and third-party data sources into graph-based platforms using scalable data engineering patterns.
Partner with Architecture, Product, AI Platform, and Data Engineering organizations to align platform investments with enterprise priorities and future AI initiatives.
Drive technical direction for semantic routing, graph-powered retrieval, enterprise search, agent orchestration, and federated knowledge access patterns.
Lead evaluation, selection, and adoption of graph technologies, semantic platforms, vector databases, and AI infrastructure required to support enterprise-scale workloads.
Define and drive the strategy for AI-powered developer tooling, engineering automation, and productivity platforms that leverage technologies such as Claude, Cursor, Windsurf, AI Agents, MCP frameworks, and related AI ecosystems.
Lead teams in productionizing AI-enabled engineering solutions, ensuring scalability, security, governance, reliability, and measurable productivity improvements.
Provide technical leadership and architectural guidance across PMTS, LMTS, SMTS, and contractor teams while driving alignment across multiple organizations.
Serve as the primary technical authority for complex architectural decisions, platform investments, and long-term engineering strategy.
Foster innovation and continuous improvement while establishing a culture of engineering excellence, technical rigor, and operational maturity.

Requirements

What you’ll need

12+ years of experience in software engineering, data engineering, distributed systems, enterprise data platforms, or related technical domains
A related technical degree required.
Proven experience defining and delivering enterprise-scale Knowledge Graph platforms supporting AI, semantic search, data integration, and agentic applications.
Deep expertise in Knowledge Graph technologies, ontology engineering, semantic modeling, linked data, graph databases, and enterprise metadata management.
Strong hands-on experience with graph technologies such as Neo4j, TopQuadrant, RDF/OWL, SPARQL, property graph models, semantic reasoning frameworks, or similar technologies.
Proven experience leading the architecture and implementation of graph-powered AI solutions, semantic retrieval systems, vector search platforms, RAG architectures, and agentic workflows.
Demonstrated success in building, scaling, and productionizing AI-powered developer tools, engineering platforms, or automation solutions using technologies such as Claude, Cursor, Windsurf, GitHub Copilot, AI agents, MCP frameworks, or similar ecosystems.
Strong experience designing enterprise data engineering architectures, including large-scale ingestion, transformation, orchestration, metadata management, and data governance frameworks.
Experience with cloud-native architectures and platforms including AWS, GCP, or Azure.
Strong understanding of distributed systems, APIs, microservices, event-driven architectures, and modern software engineering practices.
Demonstrated ability to influence senior technical leaders, executives, architects, and cross-functional stakeholders.
Proven track record of defining technical strategy and driving execution across multiple teams and organizations.
Excellent communication, leadership, and stakeholder management skills.

Benefits

Comp & perks

time off programs
medical, dental, vision
mental health support
paid parental leave
life and disability insurance
401(k)
employee stock purchasing program

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills & Tools

knowledge graph technologiesontology engineeringsemantic modelinglinked datagraph databasesenterprise metadata managementdata integrationAI-powered developer toolsdata engineering architecturescloud-native architectures

Soft Skills

leadershipcommunicationstakeholder managementinfluenceinnovationcontinuous improvementtechnical authorityarchitectural guidancecollaborationstrategic thinking