data
Posted Jun 16Enterprise Application Data Architect, GTM Systems
at openai
San Francisco, United StatesHybrid
Responsibilities
- - 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.
- - 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.
Requirements
- 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.
- experience improving complex CRM environments.
- - Assess and improve Salesforce data across the lead-to-support lifecycle.
- 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 reverse-ETL integrations. - Have advanced SQL skills. - Understand relational databases, cloud data warehouses, APIs, data pipelines, integration platforms, and distributed data systems. - 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
Additional details
- 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.
- 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.
- 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.
- - Establish matching, merging, and survivorship rules for people, companies, accounts, and related records.
- - 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