Principal Architect - Data

Job Summary
The Principal Architect (Data) is a senior technical leader responsible for defining and advancing enterprise data architecture strategy. Focusing on data platforms, integration, governance, analytics, and information security, this role plays a key part in defining how data is structured, managed, and utilized across the organization.
Serving as a trusted authority on enterprise data practices, the Principal Architect establishes standards for data quality, interoperability, and lifecycle management, while driving innovation in data enablement. Ensuring ongoing alignment with evolving regulatory and legal data requirements by proactively interpreting mandates, embedding compliance into architectural standards, and guiding the organization in adopting consistent approaches to data identification, classification, and protection across the enterprise.
Operating as a core member of a broader team of Principal Architects, this role collaborates closely with peers to align on standards, exchange best practices, and collectively drive a cohesive, enterprise-wide architectural vision. Recognized as an expert both internally and externally, this role sets the direction for scalable, secure, and business-aligned data architecture that supports most impactful initiatives.
Primary Responsibilities
Enterprise-Wide Architectural Data Leadership

• Define and evolve the enterprise data architecture across key data domains, including data platforms, integration, governance, analytics, and data security, ensuring cohesive and scalable end-to-end data solutions.
• Act as the lead architect for enterprise data initiatives and programs, aligning data strategy and investments with long-term business and operational objectives.
• Drive the integration and accessibility of data across applications and platforms to enable trusted, high-quality, and future-ready data capabilities.
• Align data governance with applicable regulatory and compliance frameworks, including data privacy and cybersecurity requirements, and proactively identify and mitigate risks across data assets and data flows to ensure adherence to legal, privacy and security standards.

Vision and Strategy Development

• Shape enterprise data strategy with a 3–5-year horizon, aligning data platforms, governance, and analytics capabilities with evolving business priorities and emerging trends.
• Identify and champion innovative data initiatives that drive transformational value and position to lead in data-driven decision-making.
• Design and evolve the data strategy to proactively address emerging technologies, such as Artificial Intelligence (AI) and agentic workflows.
• Anticipate how these innovations will impact data architecture, governance, and security, and embed them into a forward-looking strategy that enables scalable, responsible, and business-aligned adoption across the enterprise.
• Lead the development of data architecture contributions as an integral component of the broader enterprise architecture strategy, ensuring alignment with organizational priorities while ensuring data is treated as a core enterprise asset.

Innovation and Influence

• Drive innovative data solutions that unlock new insights and create sustained strategic advantage.
• Elevate enterprise data capabilities by promoting best practices in data architecture, governance, and analytics, while fostering a culture of continuous improvement and experimentation.
• Extend influence beyond the organization by collaborating with corporate partners to define and deliver data exchange solutions that enable secure, scalable, and governed data sharing across ecosystems.

Solution Design and Problem Solving

• Independently address complex data architecture and integration challenges, including those involving emerging data technologies and unproven approaches.
• Design and implement enterprise-scale data solutions that span multiple systems and data domains, ensuring seamless data integration and interoperability.
• Ensure all data architecture designs prioritize scalability, data quality, resilience, and long-term sustainability to support evolving business needs.

Communication and Leadership

• Clearly articulate complex data concepts, architecture, and strategy to a wide range of audiences, including executives, business stakeholders, and technical teams.
• Collaborate closely with peer architects to align on enterprise standards, share insights, and ensure a cohesive, cross-domain architectural approach.
• Develop and deliver data-focused documentation, standards, and roadmaps tailored to both technical and non-technical audiences.
• Provide leadership, coaching, and mentorship to teams across IT, promoting best practices in data architecture, governance, and data-driven decision-making.

External Engagement and Advocacy

• Represent in data and analytics conferences, panels, and industry forums to elevate the organization's leadership in enterprise data architecture.
• Build and maintain strong relationships with peers, technology partners, and academic institutions to bring emerging data practices and innovations
• Strengthen reputation as a leader in data and analytics to attract top-tier data architecture and engineering talent.

Job Requirements
To perform this job successfully, an individual must be able to perform each essential duty satisfactorily. The requirements listed below are representative of the knowledge, skill, and/or ability required. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.
Education

• Bachelor's Degree in a related field of study – Required Or
• H.S. Diploma and equivalent experience in lieu of degree – Required

Work Experience

• At least 12-15 years of relevant and progressive work experience – Required

Skills & Personal Qualifications

• Data Architecture Expertise: Demonstrates deep, authoritative knowledge across enterprise data domains with a proven ability to design and integrate complex, cross-functional data solutions. Strong expertise in modern cloud data technologies across AWS and Azure, including data platforms, data integration and engineering, analytics, governance, security and AI/ML capabilities. Deep experience with architectural data patterns such as data lakes, lakehouse architectures, data warehousing, data streaming, real-time and event-driven processing, and ETL/ELT pipelines, along with metadata management, data cataloging, and master data management (MDM). Applies a security-first approach to data architecture by embedding protection, privacy, and controls into data solutions. Ensures use of emerging technologies such as AI and agentic workflows are securely integrated, governed, and aligned with enterprise standards. Proven track record in establishing data architecture standards, governance frameworks, and reusable patterns that promote consistency, scalability, and effective data management across the enterprise.
• Strategic and Conceptual Thinking: Anticipates emerging trends in data, analytics, and technology, and translates them into actionable enterprise data architecture strategies. Demonstrates the ability to conceive and lead initiatives that transform how data is managed, integrated, and leveraged to drive business capabilities and modernize data delivery models.
• Enterprise Data Strategy Development: Demonstrates the ability to design and implement comprehensive data strategies that support diverse use cases, including analytics, real-time transactional processing, bulk data movement, and API-driven data access. Ensures each data pattern is backed by appropriate architecture, technologies, and governance to enable scalable, reliable, and secure data flows across the enterprise. Aligns data capabilities with business priorities to support consistent, high-quality data that supports both operational systems and advanced analytics.
• Data Protection, Privacy, and Compliance Proficiency: Demonstrates knowledge of data privacy and security requirements, workflows, and strategies for data protection including tagging, encryption, pseudonymization, and masking, as well as data destruction processes for security and privacy compliance. Ability to support and enforce Data Loss Prevention (DLP) strategies and tools across the enterprise.
• Hands-On Technical Proficiency: Maintains the ability to work hands-on when needed, leveraging modern programming languages and data tools to support investigation, proof-of-concept (POC) development, and rapid prototyping. Capable of diving into code to validate architectural decisions, troubleshoot complex data challenges, and accelerate innovation.
• Communication and Influence: Demonstrates mastery in written and verbal communication skills, able to engage effectively with both senior leadership and technical teams. Skilled in collaborating with a broader community of architects to align on architectural direction, share best practices, and drive cohesive outcomes. Comfortable advocating for technical change and persuading stakeholders across organizational boundaries.
• Leadership Through Networks: Demonstrates leadership in matrixed environments with the ability to lead through influence rather than direct authority. Experience forming and leading communities of practice or cross-functional architecture working groups.
• Innovation and Industry Engagement: Recognized leader in enterprise data architecture, with external visibility through thought leadership, speaking engagements, and contributions to the data and analytics community. Demonstrates a strong passion for advancing modern data technologies and applying them in innovative ways to transform how data is managed, governed, and utilized within the enterprise.
• Business and Competitive Insights: Demonstrates a deep understanding of business operations and how data enables competitive advantage. Ability to incorporate industry trends, benchmarking, and data-driven insights into enterprise data architecture, ensuring strategies and solutions that enhance business outcomes and inform strategic decision-making.