Description
The Chief Data Officer's (CDO) organization (Data Solutions) is at the epicenter of Salesforce's data-driven transformation to build the agentic enterprise and enable effective decision making for the enterprise. We are seeking a world-class data modeling practice leader to build and manage the data models that power our business.
The Senior Director, Data Modeling is a senior, hands-on leadership role responsible for building and managing the enterprise data modeling practice. This leader and their team are the company's central experts on how to effectively implement data models that span our complex, hybrid-cloud ecosystem.
This role's primary focus is on the practical design, implementation, and optimization of data models that run on our established enterprise data platforms. Your mission is to lead the practice of applied data modeling, maximizing the value and performance of our existing data ecosystem. You will be responsible for designing and governing the optimal data models that span our complex environment, including Salesforce Data360 (formerly Data Cloud), Snowflake, Amazon data lakes, multiple Salesforce orgs, Informatica MDM, graph databases, and vector databases.
Your primary stakeholders are the Data Science, Automation, and Application teams within Data Solutions and the larger Digital Enterprise Technology organization. You will partner directly with them to understand their requirements and lead your team to build the performant, scalable, and secure data models they need to succeed. You must be an expert in the benefits and trade-offs of every modeling choice, from logical design to physical implementation, across our entire data landscape.
Responsibilities
Modeling Practice & Team Leadership:
Lead, mentor, and grow a high-performing, globally-distributed team of data modelers.
Define and own the enterprise-wide standards, processes, and best practices for the implementation of all data models within the enterprise data platforms and enterprise architecture practices
Stakeholder-Driven Model Design:
Serve as the primary partner and consultant for Data Science, Automation, and Application teams.
Translate their functional and non-functional requirements (e.g., analytical performance, query latency, automation throughput) into optimal logical and physical data model designs.
Hybrid-Cloud Model Implementation:
Design and govern the implementation of data models that span our hybrid ecosystem, including Salesforce Data 360, multiple Salesforce orgs, Informatica MDM, Amazon data lakes, and Snowflake.
Master the benefits and trade-offs of modeling on each platform, such as leveraging Snowflake's zero-copy data sharing vs. federating queries to S3.
Advanced Modeling Expertise:
Lead the design and modeling for the Enterprise Knowledge Graph, partnering with the platform team on its implementation on our chosen graph database.
Design and govern the data models that integrate unstructured data and vector embeddings (from our vector database) with our core enterprise structured data.
Data Modeling Design Authority:
Serve as the chief arbiter and thought leader on data modeling methodologies. Drive the strategic selection and implementation of the right model for the right stakeholder.
You must be the expert on the practical implementation of data modeling approaches such as 3NF, Data Vault 2.0, and Star/Snowflake schemas, and be able to defend your choice based on performance, cost, and maintainability.
Required Qualifications
Experience: 12+ years of hands-on data modeling, with at least 7+ years in a senior leadership role managing technical modeling teams.
Modeling Methodology Expert: Expert-level mastery of all major data modeling methodologies and the deep implementation trade-offs between them such as 3NF (for applications), Data Vault (for integration layers), and Star/Snowflake schemas (for data science).
Hybrid-Cloud Modeling Expertise: Proven, hands-on experience building and optimizing data models on a complex, hybrid-cloud stack. Mandatory expertise with Snowflake and demonstrable experience modeling data across Amazon data lakes (e.g., S3).
Master Data Management (MDM): Deep experience modeling Master Data Management golden records and hierarchies, and integrating them with operational and analytical systems (e.g., Informatica MDM).
Salesforce Ecosystem Expertise: Deep understanding of the data modeling challenges within a multi-org Salesforce CRM environment and a customer activation platform (Salesforce Data Cloud canonical model DLO/DMO).
Enterprise Graph Modeling: Proven, deep experience designing and modeling enterprise-scale Knowledge Graphs for implementation on graph databases.
AI & Modern Data Expertise: Demonstrable experience with modeling unstructured data and designing the models to integrate vector embeddings from a vector database into a cohesive enterprise view.
Stakeholder-Driven Leadership: A proven track record of partnering directly with Data Science, Automation, and Application/Engineering teams to deliver data models that meet their specific needs.
Data Governance Partnership: Proven experience partnering with Data Governance teams to ensure models are compliant, secure, and integrated with the enterprise data catalog.
Collaboration & Influence: Exceptional communication skills. The ability to articulate complex implementation trade-offs (e.g., "why this join strategy in Snowflake is better for your DS model") to both technical and non-technical stakeholders.
Preferred Qualifications
Salesforce Data Cloud / Data 360 Expertise: Deep understanding of Salesforce Data 360 platform with experience designing, deploying, and managing data model objects on enterprise deployments of Salesforce Data 360
Data Modeling Certifications: Relevant industry standard data certifications for Data Management professionals and cloud database management from Amazon, Snowflake, Google, Neo4J, or similar. Formal training in all major modeling methodologies (Kimball, Inmon, etc.) to demonstrate a "toolbox" approach
Data Mesh: Familiarity with Data Mesh principles and how different modeling standards serve as the foundation for interoperable data products.
For roles in San Francisco and Los Angeles: Pursuant to the San Francisco Fair Chance Ordinance and the Los Angeles Fair Chance Initiative for Hiring, Salesforce will consider for employment qualified applicants with arrest and conviction records.