# Enterprise Application Data Architect, GTM Systems

**Company:** [OpenAI](https://hotfix.jobs/companies/openai)
**Location:** San Francisco, CA
**Role:** Data Engineering
**Salary:** $260k – $288k/yr
**Experience:** 7+ years
**Skills:** Salesforce, SQL, Data Modeling, Master Data Management, Data Governance, ETL, API Integrations, Cloud Data Warehouses, Data Quality, Identity Resolution
**Posted:** 2026-06-16

> Define and improve data architecture for GTM systems and enterprise CRM. Lead Salesforce data modeling, integrations, governance, and quality initiatives across the customer lifecycle.

## Job Description

## 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

## 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

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