Enterprise Application Data Architect, Gtm Systems

OpenAI OpenAI · AI Frontier · San Francisco, CA · Finance

This role focuses on defining and improving the data architecture for go-to-market systems and enterprise CRM environments. It involves designing scalable data models, establishing system-of-record definitions, improving integrations, and leading data quality and governance initiatives across the customer lifecycle. The role requires expertise in enterprise data architecture, data management, and CRM systems, with a focus on translating business requirements into technical solutions.

What you'd actually do

  1. Define the target architecture for customer, account, contact, lead, opportunity, activity, campaign, and support data.
  2. Assess and improve Salesforce data across the lead-to-support lifecycle.
  3. Design canonical data models, entity relationships, identity-resolution rules, and system-of-record definitions.
  4. Lead data-cleansing and remediation initiatives, including deduplication, normalization, enrichment, validation, and historical cleanup.
  5. Establish matching, merging, and survivorship rules for people, companies, accounts, and related records.

Skills

Required

  • enterprise data architecture
  • data management
  • data engineering
  • Salesforce data architecture
  • data modeling
  • integration design
  • data governance
  • SQL
  • relational databases
  • cloud data warehouses
  • APIs
  • data pipelines
  • integration platforms
  • distributed data systems
  • data quality rules
  • observability controls
  • reconciliation processes
  • service-level expectations
  • technical leadership

Nice to have

  • master data management
  • identity resolution
  • entity matching
  • deduplication
  • metadata management
  • data lineage
  • batch integrations
  • API-based integrations
  • event-driven integrations
  • reverse-ETL
  • Salesforce
  • Clay
  • PitchBook
  • ZoomInfo
  • HG Insights
  • Cognism
  • Harmonic
  • Meticulate
  • sales intelligence platforms
  • enrichment platforms
  • company-data platforms
  • prospecting platforms
  • go-to-market automation platforms
  • CRM data integration
  • business intelligence environments
  • data contracts
  • schema versioning
  • change-data capture
  • event-driven architecture
  • privacy requirements
  • security requirements
  • retention requirements
  • communication skills
  • cross-functional program leadership
  • data modernization programs
  • CRM transformation programs
  • enterprise data-governance programs

What the JD emphasized

  • strong technical expertise in enterprise data architecture
  • hands-on experience improving complex CRM environments
  • deep expertise in enterprise data architecture, data management, data engineering, or a related technical discipline
  • strong hands-on experience with Salesforce data architecture
  • successfully cleaned, restructured, or migrated large and complex enterprise CRM datasets