Enterprise Application Data Architect, GTM Systems

OpenAI•San Francisco, CA

3d•$260,000 - $288,000•Hybrid

About The Position

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. 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.

Requirements

Deep expertise in enterprise data architecture, data management, data engineering, or a related technical discipline.
Strong hands-on experience with Salesforce data architecture, including leads, contacts, accounts, opportunities, activities, campaigns, and support-related objects.
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.
Experience designing batch, API-based, event-driven, and reverse-ETL integrations.
Advanced SQL skills.
Understand relational databases, cloud data warehouses, APIs, data pipelines, integration platforms, and distributed data systems.
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.
Experience with Salesforce and several of the following platforms: Clay, PitchBook, ZoomInfo, HG Insights, Cognism, Harmonic, and Meticulate.
Comparable experience with sales intelligence, enrichment, company-data, prospecting, or go-to-market automation platforms.
Experience integrating CRM data with cloud data warehouses and business intelligence environments.
Familiar with data contracts, schema versioning, change-data capture, and event-driven architecture.
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.
Led cross-functional data modernization, CRM transformation, or enterprise data-governance programs.

Responsibilities

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.