Principal Data Architect

• Job: 35921-MCAR
• Team: Business Applications and Tools
• Location: US-MA-Natick
• Salary Range: USD 140,000 - 224,000

• Define the target-state Data and AI architecture aligned with business goals and technology strategy.
• Establish architectural standards, principles, and best practices across the data ecosystem.
• Develop and maintain a multi-year roadmap covering data platforms, integrations, and AI enablement.
• Design scalable, secure, and interoperable data architectures that support enterprise analytics, operational reporting, and AI-driven use cases.

• Define enterprise AI data readiness strategies to ensure data is accessible, trusted, and AI-ready.
• Assess and improve data maturity across structured and unstructured data, including metadata, semantic models, lineage, and quality.
• Design scalable architecture and reusable patterns for AI, machine learning, advanced analytics, and automation.
• Collaborate with business, analytics, and AI teams to identify data gaps and prioritize improvements.
• Define architectural standards for RAG, vector databases, knowledge repositories, and enterprise AI platforms.
• Establish standards for metadata, observability, discoverability, and data products to maximize AI adoption and business value.
• Evaluate emerging AI technologies and recommend solutions that improve scalability, performance, and time-to-value.
• Incorporate responsible AI principles, including transparency, explainability, traceability, and auditability, into solution designs.

• Partner closely with business and technical stakeholders to understand needs, define requirements, and co-create data solutions that deliver measurable outcomes.
• Translate complex technical concepts into clear, executive-ready communication.
• Provide architectural leadership and thought partnership across cross-functional teams.
• Strong ability to influence stakeholders and drive outcomes without formal authority.

• A bachelor's degree and 10 years of professional work experience (or equivalent experience) is required.
• Experience with data architecture

• Experience in enterprise data architecture, data management, analytics platforms, and AI-enabled data ecosystems.
• Demonstrated success leading large, complex, cross-functional data initiatives.
• Strong ability to influence stakeholders and drive outcomes without formal authority.
• Analytical and structured thinker—comfortable navigating ambiguity and solving complex data problems.
• Highly self-directed, organized, and capable of independently driving strategic and technical workstreams.
• Deep understanding of AI data readiness principles, including metadata management, data products, semantic layers, data lineage, and AI-ready data architectures.
• Experience implementing data localization, data residency, or data sovereignty requirements across global environments.