Salesforce · 1 week ago
Principal Data Modeler
Washington - Seattle
Full-time
Hybrid
Lead/Staff
$197K/yr - $314K/yr
10+ years expSalesforce is the #1 AI CRM, focused on driving customer success through innovation and technology. The Principal Data Modeler will be responsible for designing and managing the data models for the Marketing Data Warehouse, ensuring the architecture is scalable and high-performing, while collaborating with various teams to support data-driven decisions in marketing.
Agentic AIArtificial Intelligence (AI)Cloud ComputingCRMSaaSSales EnablementSoftware
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's zero-copy data sharing vs. federating queries to S3
Enforce rigorous data cataloging and metadata standards to ensure all marketing metrics have a single, unambiguous definition across the organization
Collaborate with other Data and Application Architects to ensure the data warehouse model aligns with the overall enterprise data strategy and upstream/downstream system architectures
Ensure the data model is intuitive and accessible for all Data Scientists, Analysts, Data and BI Engineers who build curated datasets, predictive models, and dashboards to measure and optimize marketing performance
Qualification
Required
Master's or Ph.D in Computer Science, Information Systems, or a related quantitative field
10+ years of hands-on data modeling, data architecture, or database design experience
5+ years of experience designing and implementing large-scale Enterprise Data Warehouses
Expert-level knowledge of dimensional modeling (Star/Snowflake schemas) and its application to business intelligence, reporting, and machine learning workloads including feature engineering for workloads such as attribution models, lead scoring, and propensity models
Extensive experience with marketing data domains (e.g., campaign management, CRM, web analytics, attribution/marketing mix modeling, propensity modeling, forecasting, and optimization). Demonstrated ability to model complex business processes, including slowly changing dimensions and historical data tracking
Proven, hands-on experience building and optimizing data models on a modern, cloud-native data warehouse platform, with deep expertise in Snowflake
Advanced proficiency with SQL and DDL/DML, especially optimized for the Snowflake ecosystem. Familiarity with ETL tools (e.g., dbt, Fivetran), cloud services (AWS, GCP, or Azure), and how to design data models that optimize their performance
Expert-level mastery of all major data modeling methodologies and implementation trade-offs between them such as 3NF (for applications), Data Vault (for integration layers), and Star/Snowflake schemas (for data science)
Deep experience modeling Master Data Management golden records and hierarchies, and integrating them with operational and analytical systems (e.g., Informatica MDM)
Experience implementing Data Mesh principles: domain ownership of data products, 'data as a product' mindset with clear SLAs and documentation, and federated governance that balances central standards with domain autonomy
Experience designing data models that support ML feature engineering, including feature stores and feature registries. Understanding of how data modeling decisions impact feature freshness, model training pipelines, and real-time inference
A proven track record of partnering directly with Data Engineering, Data Science, and Machine Learning Engineering teams to deliver data models that meet their specific needs. Must thrive in a high-velocity environment with rapid iteration cycles and be able to balance governance requirements with engineering agility
Experience partnering with Data Governance teams to ensure models are compliant, secure, and integrated with the enterprise data catalog
Exceptional communication skills. The ability to lead technical design discussions and articulate complex technical concepts and implementation trade-offs to both technical and business stakeholders
Highly organized and meticulous, with a passion for data accuracy and structural integrity
Preferred
Knowledge of Salesforce Data 360 platform with experience designing, deploying, and managing data model objects on enterprise deployments of Salesforce Data 360 is highly desirable
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)
Benefits
Time off programs
Medical
Dental
Vision
Mental health support
Paid parental leave
Life and disability insurance
401(k)
Employee stock purchasing program
Company
Salesforce
Salesforce is a cloud-based software company that provides customer relationship management software and applications.
10001+ employees
H1B Sponsorship
Salesforce has a track record of offering H1B sponsorships. Please note that this does not
guarantee sponsorship for this specific role. Below presents additional info for your
reference. (Data Powered by US Department of Labor)
Distribution of Different Job Fields Receiving Sponsorship
Represents job field similar to this job
Trends of Total Sponsorships
2025 (1883)
2024 (2296)
2023 (1850)
2022 (2849)
2021 (2124)
2020 (1960)
Funding
Current Stage
Public CompanyTotal Funding
$65.38MKey Investors
Starboard ValueEmergence CapitalHalsey Minor
2022-10-18Post Ipo Equity
2004-06-23IPO
2003-01-01Series Unknown· $1M
Leadership Team
Arundhati Bhattacharya
Chairman & Ceo Salesforce India
Marc Benioff
Chair & CEO
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