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Enterprise Application Data Architect, GTM Systems

Openai
CompanyOpenai
CategoryEngineering
LocationSan Francisco
RemoteHybrid
EmploymentNot stated
LevelLead
SalaryUSD 260k–288k
Posted16 Jun 2026
Last verified2 Aug 2026
SourceEmployer ATS (ashby)
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Description
About the Team The Growth and Support Services team is responsible for building and maintaining the systems, data foundations, and operational processes that support our go-to-market and customer-facing teams. The team partners closely with Revenue Operations, Business Systems, Data Engineering, Analytics, Sales, Marketing, Customer Success, Support, Security, and other cross-functional stakeholders. Our work helps ensure that customer and prospect data is accurate, consistent, secure, and actionable across the full customer lifecycle. About the Role As a Data Architect, you will define and improve the data architecture supporting our go-to-market systems and enterprise CRM environment. You will lead efforts to improve Salesforce and internal data from initial lead acquisition and enrichment through sales, onboarding, customer success, and support. You will design scalable data models, establish system-of-record definitions, improve integrations, and lead data-quality and governance initiatives across customer, account, contact, lead, opportunity, and support data. We’re looking for people who combine strong technical expertise in enterprise data architecture with hands-on experience improving complex CRM environments. You should be comfortable working across architecture, data modeling, integration design, governance, and implementation. This role is based in San Francisco, CA. We use a hybrid work model of three days in the office per week and offer relocation assistance to new employees. In this role you will: - Define the target architecture for customer, account, contact, lead, opportunity, activity, campaign, and support data. - Assess and improve Salesforce data across the lead-to-support lifecycle. - Design canonical data models, entity relationships, identity-resolution rules, and system-of-record definitions. - Lead data-cleansing and remediation initiatives, including deduplication, normalization, enrichment, validation, and historical cleanup. - Establish matching, merging, and survivorship rules for people, companies, accounts, and related records. - Architect integrations between Salesforce, data warehouses, operational systems, support platforms, and third-party data providers. - Define standards for field definitions, lifecycle stages, ownership, metadata, lineage, retention, and access controls. - Implement automated monitoring for data quality, completeness, freshness, consistency, and integration failures. - Improve the flow of data between marketing, sales, customer success, and support systems. - Evaluate third-party data sources and define how external data should be matched, validated, and incorporated into enterprise systems. - Partner with Business Systems, Revenue Operations, Data Engineering, Analytics, Security, and business stakeholders to translate operational requirements into durable technical solutions. - Produce architecture diagrams, data dictionaries, integration specifications, governance documentation, and implementation guidance. - Provide technical leadership and guide teams through complex data architecture and system-design decisions. - Support and improve integrations involving Salesforce and go-to-market data platforms such as Clay, PitchBook, ZoomInfo, HG Insights, Cognism, Harmonic, and Meticulate. You might thrive in this role if you: - Have deep expertise in enterprise data architecture, data management, data engineering, or a related technical discipline. - Have strong hands-on experience with Salesforce data architecture, including leads, contacts, accounts, opportunities, activities, campaigns, and support-related objects. - Have successfully cleaned, restructured, or migrated large and complex enterprise CRM datasets. - Understand master data management, identity resolution, entity matching, deduplication, metadata management, data lineage, and data governance. - Have experience designing batch, API-based, event-driven, and rev
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