Principal Data Modeler

To get the best candidate experience, please consider applying for a maximum of 3 roles within 12 months to ensure you are not duplicating efforts. Job Category Data Job Details 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. Ready to level-up your career at the company leading workforce transformation in the agentic era? You’re in the right place! Agentforce is the future of AI, and you are the future of 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. Agentforce is the future of AI, and you are the future of Salesforce! The Marketing Data Science team within Salesforce’s Chief Data Office is seeking an experienced data modeler to build and manage the data model(s) for our Marketing Data Warehouse. This role is crucial for enabling data-driven decisions across Marketing and will be the technical authority for all data modeling efforts, ensuring the warehouse architecture is scalable, high-performing, and accurately reflects the complex relationships within our rich B2B marketing data ecosystem (including campaigns, channels, leads, customer journeys, opportunities, etc.) This role's primary focus is on the practical design, implementation, and optimization of the data models for the Marketing Data Warehouse. It will be responsible for designing and governing the optimal data models that span our complex data environment, hybrid-cloud ecosystem, including Salesforce Data 360 (formerly Data Cloud), Snowflake, Amazon data lakes, multiple Salesforce orgs, Informatica MDM, and graph databases. A key success factor is designing models that serve both analytical reporting and machine learning workloads, including feature engineering for ML models and real-time scoring systems. Your primary stakeholders would be the Data Science, Analytics, Data Engineering, and Marketing Automation teams that support the Salesforce’s Marketing organization. You will build the performant, scalable, and secure data models, while thoughtfully weighing the trade-offs of every modeling choice, from logical design to physical implementation. Key Role Responsibilities Design and implement a robust data model that integrates data from core B2B systems, including Snowflake, Salesforce Data 360, multiple Salesforce orgs, Informatica MDM, and Amazon data lakes. Design and evolve scalable end-to-end data architecture; define standards for data modeling, ingestion framework, pipelines, data quality, etc. Architect tables and views to clearly define and calculate critical metrics (e.g., lead conversion, MQL, marketing driven pipe, ROI). Translate business needs for marketing performance measurement, customer segmentation, targeting, and personalization into precise data requirements and model designs.Translate functional and non-functional requirements (e.g., analytical performance, query latency, automation throughput) into optimal logical, conceptual, and physical data model designs. Partner with Data Engineering to design data models that leverage advanced Snowflake features (e.g., clustering keys, materialized views, micro-partitions, time travel) to optimize query performance and cost efficiency. Master the benefits and trade-offs of modeling on each platform, such as leveraging Snowflake ... (truncated, view full listing at source)