Enterprise Application Data Architect, GTM Systems
WFA Digital Insight
The demand for skilled data architects has grown exponentially in recent years, with a 27% increase in job openings in 2025 alone. As companies like Openai continue to expand their operations, the need for experts who can design and maintain complex CRM systems has become paramount. With the rise of remote work, data architects can now work with global teams and contribute to the development of innovative technologies. Before applying, candidates should be aware of the importance of staying up-to-date with the latest industry trends and technologies, as well as the need for strong communication skills to collaborate with cross-functional teams.
Job Description
About the Role
The Enterprise Application Data Architect plays a crucial role in defining and improving the data architecture supporting Openai's go-to-market systems and enterprise CRM environment. This role requires a deep understanding of enterprise data architecture, data management, and data engineering, as well as hands-on experience with Salesforce data architecture. The ideal candidate will have a strong technical expertise and be able to lead efforts to improve Salesforce and internal data from initial lead acquisition and enrichment through sales, onboarding, customer success, and support.The Growth and Support Services team is responsible for building and maintaining the systems, data foundations, and operational processes that support Openai's go-to-market and customer-facing teams. As a Data Architect, you will partner closely with Revenue Operations, Business Systems, Data Engineering, Analytics, Sales, Marketing, Customer Success, Support, Security, and other cross-functional stakeholders to ensure that customer and prospect data is accurate, consistent, secure, and actionable across the full customer lifecycle.
What You Will Do
- 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
What We Are Looking For
- 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
- Experience cleaning, restructuring, or migrating large and complex enterprise CRM datasets
- Understanding of 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
- Strong communication and collaboration skills
Nice to Have
- Experience with data visualization tools and techniques
- Knowledge of machine learning and artificial intelligence concepts
- Familiarity with cloud-based data platforms and services
- Certification in data architecture or a related field
Benefits and Perks
- Competitive salary and benefits package
- Opportunity to work with a cutting-edge technology company
- Collaborative and dynamic work environment
- Professional development and growth opportunities
- Flexible working hours and remote work options
- Access to the latest tools and technologies
- Recognition and reward for outstanding performance
How to Stand Out
- Familiarize yourself with Openai's technology stack and be prepared to discuss your experience with similar tools and systems
- Highlight your expertise in data architecture and management, and be prepared to provide specific examples of your experience
- Showcase your ability to communicate complex technical concepts to non-technical stakeholders
- Be prepared to discuss your experience with data quality and governance initiatives
- Research the company culture and values, and be prepared to discuss how you align with them
- Prepare to discuss your experience with remote work and collaboration tools
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