Enterprise Application Data Architect, GTM Systems

Compensation

The base pay offered may vary depending on multiple individualized factors, including market location, job-related knowledge, skills, and experience. The salary range for this role is $260K – $288K.

Benefits

• Medical, dental, and vision insurance for you and your family, with employer contributions to Health Savings Accounts
• Pre-tax accounts for Health FSA, Dependent Care FSA, and commuter expenses (parking and transit)
• 401(k) retirement plan with employer match
• Paid parental leave (up to 24 weeks for birth parents and 20 weeks for non-birthing parents), plus paid medical and caregiver leave (up to 8 weeks)
• Paid time off: flexible PTO for exempt employees and up to 15 days annually for non-exempt employees
• 13+ paid company holidays, and multiple paid coordinated company office closures throughout the year for focus and recharge, plus paid sick or safe time
• Mental health and wellness support
• Employer-paid basic life and disability coverage
• Annual learning and development stipend to fuel your professional growth
• Daily meals in our offices, and meal delivery credits as eligible
• Relocation support for eligible employees

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.

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.