Enterprise Application Data Architect, GTM Systems
OpenAI
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Compensation
Salary & market context
267% above the BLS national median
BLS national median: $74,680
Requirements
Top requirements
- We’re looking for people who combine strong technical expertise in enterprise data architecture with hands-on experience improving complex CRM environments.
- 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 reverse-ETL integrations. - Have advanced SQL skills. - Understand relational databases, cloud data warehouses, APIs, data pipelines, integration platforms, and distributed data systems. - Have experience defining data-quality rules, observability controls, reconciliation processes, and measurable service-level expectations. - Can translate business processes and operational requirements into scalable technical models and architecture. - Have experience with Salesforce and several of the following platforms: Clay, PitchBook, ZoomInfo, HG Insights, Cognism, Harmonic, and Meticulate. - Have comparable experience with sales intelligence, enrichment, company-data, prospecting, or go-to-market automation platforms. - Have experience integrating CRM data with cloud data warehouses and business intelligence environments. - Are familiar with data contracts, schema versioning, change-data capture, and event-driven architecture. - Have experience managing sensitive customer and prospect data in accordance with privacy, security, and retention requirements. - Communicate complex technical decisions clearly to both technical and non-technical audiences. - Have led cross-functional data modernization, CRM transformation, or enterprise data-governance programs.
- AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity.
Perks & setup
Benefits candidates care about
- About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity.
Why candidates care
Benefits & perks
- About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity.
Start here
Requirements
- We’re looking for people who combine strong technical expertise in enterprise data architecture with hands-on experience improving complex CRM environments.
- 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 reverse-ETL integrations. - Have advanced SQL skills. - Understand relational databases, cloud data warehouses, APIs, data pipelines, integration platforms, and distributed data systems. - Have experience defining data-quality rules, observability controls, reconciliation processes, and measurable service-level expectations. - Can translate business processes and operational requirements into scalable technical models and architecture. - Have experience with Salesforce and several of the following platforms: Clay, PitchBook, ZoomInfo, HG Insights, Cognism, Harmonic, and Meticulate. - Have comparable experience with sales intelligence, enrichment, company-data, prospecting, or go-to-market automation platforms. - Have experience integrating CRM data with cloud data warehouses and business intelligence environments. - Are familiar with data contracts, schema versioning, change-data capture, and event-driven architecture. - Have experience managing sensitive customer and prospect data in accordance with privacy, security, and retention requirements. - Communicate complex technical decisions clearly to both technical and non-technical audiences. - Have led cross-functional data modernization, CRM transformation, or enterprise data-governance programs.
- AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity.
Responsibilities
What you'll do
- 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.
- 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.
- You should be comfortable working across architecture, data modeling, integration design, governance, and implementation.
- 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.
Role snapshot
About the role
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.
As a Data Architect, you will define and improve the data architecture supporting our go-to-market systems and enterprise CRM environment.
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