Solutions Architect

Vizient • Irving, TX

1d • $135,200 - $236,600

About The Position

Provide architectural leadership across the Spend Data Management portfolio, supporting enterprise master data, data products, and modernization initiatives across multiple products and engineering teams. Design secure, scalable, resilient solutions for high-volume data platforms, including product and vendor mastering, APIs, integrations, cloud services, data quality, identity, security, and semantic technologies. Establish architecture standards and reusable capabilities, guide internal teams and implementation partners, and influence technical decisions that improve data availability, throughput, reliability, and long-term platform evolution.

Requirements

• 7 or more years of related experience.
• Strong architecture experience with enterprise MDM, including product and/or vendor mastering.
• Experience designing high-volume enterprise data platforms that process millions of records, with demonstrated focus on scalability, throughput, reliability, data quality, and near-real-time availability.
• Experience designing solution and reference architectures across data products, APIs, integrations, cloud platforms, event-driven systems, identity, security, and distributed services.
• Experience leading complex modernization or platform-transition initiatives involving master-data platforms, enterprise data platforms, integrations, or cloud services.
• Experience leading architecture reviews, evaluating technology and vendor options, documenting tradeoffs, and guiding production-readiness decisions.
• Ability to mentor engineers, influence technical decisions, and raise team capability without formal people-management authority.
• Knowledge of enterprise security, privacy, compliance, data governance, identity, resiliency, observability, automated testing, CI/CD, operational readiness, and modern engineering practices.

Nice To Haves

• Relevant degree preferred.
• Experience with Informatica MDM, Tibco EBX, Databricks, Snowflake, Microsoft Azure data services, Stardog, ontologies, semantic technologies, or comparable enterprise MDM and modern data platforms.

Responsibilities

• Lead adoption of the Spend Data Management data-product model by establishing standards for product ownership, consumer outcomes, interfaces, data contracts, quality, support, security, discoverability, and lifecycle management.
• Design end-to-end solution and reference architectures spanning enterprise master data, data products, applications, APIs, integrations, cloud platforms, eventing, data quality, identity, security, and semantic technologies.
• Translate business capabilities and requirements into secure, scalable, resilient architectures and reusable capabilities for master-data management (MDM), product and vendor mastering, identity resolution, data access, data quality, and stewardship workflows.
• Architect high-volume data solutions that process millions of records and improve scalability, throughput, data correctness, and near-real-time availability.
• Provide architectural leadership across multiple products and guide internal engineering teams and implementation partners through solution design, delivery, production readiness, and technical evolution.
• Partner with Product, Engineering, Platform Engineering, CloudOps, Security, Enterprise Architecture, data stewards, business stakeholders, and clients to align solutions with business and technology objectives.
• Establish and communicate architecture standards, shared services, reusable capabilities, engineering practices, data-contract standards, and reference architectures.
• Lead architecture reviews for material designs, vendor choices, integration contracts, and production-readiness decisions; document alternatives, tradeoffs, decisions, accountable owners, and follow-up actions.
• Define and govern transition architectures for modernization initiatives, including master-data platform migrations and migration from legacy enterprise data platforms to modern cloud data platforms.
• Establish minimum engineering practices for critical data flows, including automated regression and data-correctness testing, release evidence, observability, operational readiness, incident learning, and technical-debt management.
• Evaluate emerging technologies, frameworks, tools, and libraries; lead proofs of concept and reference implementations tied to business outcomes; establish guardrails for AI-assisted engineering and changes to mastered data.
• Mentor technical leads and engineers, influence technical decisions without direct authority, and advise engineering leadership on architecture readiness, material risks, investment tradeoffs, vendor dependencies, and portfolio sequencing.

Benefits

• Comprehensive benefits plan.
• Incentive eligible.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed