GTM Data Architect

Global Payments Inc.•Atlanta, GA

3d•Hybrid

About The Position

Every day, Global Payments makes it possible for millions of people to move money between buyers and sellers using our payments solutions for credit, debit, prepaid and merchant services. Our worldwide team helps over 3 million companies, more than 1,300 financial institutions and over 600 million cardholders grow with confidence and achieve amazing results. We are driven by our passion for success and we are proud to deliver best-in-class payment technology and software solutions. Join our dynamic team and make your mark on the payments technology landscape of tomorrow. The GTM Data Architect will play a critical role in designing, scaling, and optimizing how data flows through our Salesforce ecosystem to support Sales, Partner, Marketing, and Operations teams across both domestic and international markets. This role is responsible for architecting solutions that ensure accurate routing, intelligent enrichment, robust deduplication, and advanced automation within our CRM and supporting data platforms. In addition, the architect will partner closely with third-party data vendors and internal stakeholders to enable sales campaigns, improve data quality, and define how AI-driven data capabilities can be responsibly and effectively leveraged across first- and third-party data assets. This is a highly collaborative, hands-on architecture role for someone who thrives at the intersection of CRM, data platforms, orchestration tooling, and emerging AI capabilities.

Requirements

7+ years of experience in Salesforce architecture, CRM data platforms, or Revenue Operations technology.
Deep experience designing data orchestration, routing, enrichment, and deduplication at scale.
Hands-on expertise with Salesforce (Sales Cloud preferred) and complex automation frameworks.
Strong experience working with data platforms such as Snowflake and modern data pipelines.
Proven background partnering with third-party data providers and managing enrichment workflows.
Ability to translate business requirements into scalable technical architectures.
Strong collaboration and communication skills across technical and non-technical teams.

Nice To Haves

Direct experience with Ringlead Orchestration or comparable enterprise data orchestration tools.
Experience applying AI or machine learning concepts to CRM, enrichment, or go-to-market data.
Familiarity with global data privacy and compliance considerations (e.g., regional data handling).
Prior experience supporting Sales, Partner, Marketing, or Revenue Operations organizations.

Responsibilities

Architect and maintain scalable data orchestration frameworks supporting lead, account, and opportunity routing, enrichment, deduplication, and lifecycle automation within Salesforce.
Design orchestration patterns that support multi-region and international go-to-market motions, ensuring compliance with data governance and regional considerations.
Own and evolve orchestration logic leveraging tools such as but not limited to Ringlead, native Salesforce automation, and supporting services.
Partner with Revenue Operations, Sales Ops, and IT to design Salesforce data models and automation that maximize data integrity, speed-to-lead, and seller efficiency.
Collaborate on integrations between Salesforce and Snowflake, ensuring reliable data synchronization, scalable enrichment pipelines, and trusted analytics-ready datasets.
Establish best practices for data normalization, identity resolution, and deduplication across CRM and warehouse environments.
Work directly with external data vendors to source, evaluate, onboard, and operationalize enrichment data used for targeting, sales campaigns, and account intelligence.
Define enrichment strategies and success metrics to ensure data investments are measurable and aligned to revenue outcomes.
Manage vendor data ingestion and quality controls within orchestration workflows.
Help define the company’s point of view on AI’s role in data orchestration and enrichment, particularly within Revenue Operations use cases.
Explore and design AI-assisted approaches for lead scoring, routing optimization, data completeness, and predictive enrichment.
Partner with data science, analytics, and legal/compliance teams to ensure AI capabilities are responsible, explainable, and scalable.
Establish data quality standards, monitoring, and exception handling across orchestration pipelines.
Document architecture, orchestration logic, and operating standards to support long-term scalability.
Act as a subject-matter expert and advisor to Sales, Partner, Marketing, and Operations stakeholders.