Senior Director, Data Modeling

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About Salesforce

Salesforce is the #1 AI CRM, where humans with agents drive customer success together. Here, ambition meets action. Tech meets trust. And innovation isn’t a buzzword — it’s a way of life. The world of work as we know it is changing and we're looking for Trailblazers who are passionate about bettering business and the world through AI, driving innovation, and keeping Salesforce's core values at the heart of it all.

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 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.