Enterprise Architect, Data
About The Position
The Enterprise Data Architect is a senior member of Wellington Management’s Enterprise Architecture practice, shaping the firm’s data architecture direction, data platform strategy, analytics architecture, data modeling standards, and AI-enabling data capabilities. The role develops architecture strategies, roadmaps, reference architectures, patterns, standards, and technology guidance to support trusted data, scalable analytics, responsible AI, reduced complexity, managed technology risk, and optimized cost across the enterprise. The architect works with Technology Platform CIOs, the head of enterprise data, data product owners, solution architects, architecture domain working groups, data governance partners, and governance teams. The role balances strategic architecture leadership with practical solution engagement, emphasizing enterprise-level data direction, standards, reuse, governance, risk management, and long-term platform evolution. The position calls for a collaborative, credible technical leader who can translate complex data and AI architecture strategy into clear guidance for senior stakeholders and delivery teams. The architect helps teams make outcome-driven decisions that balance speed, cost, resiliency, security, data quality, responsible AI, and risk. The role also mentors architecture and engineering professionals, supports governance and technology evaluations, and helps connect enterprise direction with data, analytics, product, and AI execution.
Requirements
- Bachelor’s degree in Technology, Computer Science, Data Science, Engineering, Information Systems, Business, or a related field.
- 10 or more years of experience in technology leadership, enterprise architecture, data architecture, solution architecture, platform architecture, analytics architecture, technology strategy, or large-scale technology transformation.
- Demonstrated experience developing data architecture strategies, roadmaps, reference architectures, modeling standards, data patterns, and governance materials in a complex enterprise environment.
- Strong understanding of modern data architecture practices, including data platforms and products, data modeling, domain-driven design, API and event-driven integration, semantic layers, business intelligence, analytics engineering, cloud-native architecture, infrastructure as code, DevSecOps, AI platforms, and reusable platform services.
- Experience assessing data and technology decisions in terms of business value, trusted data, governance, risk, resiliency, security, cost, operational impact, responsible AI, and long-term maintainability.
- Ability to work effectively with senior technology leaders, product owners, solution architects, data engineers, analytics teams, risk partners, information security, infrastructure, data governance, privacy, and AI governance teams.
- Strong executive communication skills and ability to translate complex data, analytics, and AI architecture concepts into concise, business-aligned recommendations.
- Experience with architecture governance processes, architecture review boards, technology standards, non-functional requirements, data governance, technical debt management, and post-implementation validation.
- Ability to influence without relying solely on formal authority, using expertise, collaboration, follow-through, and practical judgment.
- Demonstrated ability to bring structure and clarity to ambiguous problems while maintaining momentum across multiple stakeholders and initiatives.
Nice To Haves
- Advanced degree or equivalent experience.
- Familiarity with architecture frameworks and modeling approaches, including TOGAF, Open Group standards, DAMA/DMBOK concepts, or related industry architecture and data management practices.
Responsibilities
- Develop and maintain data architecture strategies and roadmaps aligned with technology, data, AI, and business priorities.
- Translate business outcomes and analytics objectives into architecture direction, target-state designs, transition plans, and sequencing recommendations.
- Identify enterprise synergies, dependencies, constraints, and simplification opportunities across data platforms, analytics environments, integration, reporting, and AI-enabling services.
- Provide strategic guidance for data platforms, data products, semantic layers, business intelligence, data modeling, responsible AI, agentic systems, metadata, lineage, and data governance.
- Define and maintain enterprise data reference architectures, modeling standards, principles, patterns, and reusable design guidance.
- Promote governed data products, strategic platforms, reusable services, common semantic models, consistent integration patterns, and standard analytics architectures.
- Establish guidance for conceptual, logical, physical, dimensional, domain, and semantic data modeling.
- Contribute data architecture materials and governance decisions to the central architecture repository.
- Partner with platform leaders, analytics teams, product owners, technology leads, and solution architects to shape platform roadmaps and product architecture runways.
- Guide architecture for data, AI, analytics, business intelligence, API and event platforms, semantic layers, data access services, and cloud data infrastructure.
- Help delivery teams connect requirements, standards, modeling patterns, platform capabilities, governance, and execution; advise on reuse, simplification, and custom engineering.
- Support solution architects, data engineers, analytics engineers, and technical leads with solution design, non-functional requirements, integration patterns, cloud-native practices, and documentation.
- Identify opportunities to reduce duplication, retire redundant technologies, improve reuse and data quality, and align product decisions with enterprise architecture.
- Participate in Architecture Review Board and related governance processes; assess architecture risks, model gaps, data quality, metadata and lineage, technical debt, resiliency, dependencies, privacy, and security.
- Help teams prepare architecture reviews, document tradeoffs, and ensure recommendations align with business outcomes, governance expectations, and architecture principles.
- Support post-implementation architecture reviews and validations.
- Partner with technology risk, information security, infrastructure, data governance, privacy, and AI governance teams on controls, compliance, resilience, responsible AI, and operational expectations.
- Lead or contribute to technology evaluations, proofs of concept, prototypes, and industry research, and provide recommendations on build-versus-buy, platform selection, modernization, and technology lifecycle.
- Evaluate technologies for scalability, resiliency, security, observability, maintainability, cost, developer experience, data quality, metadata, lineage, governance fit, and enterprise alignment.
- Mentor architects, engineers, and technology leads; contribute to architecture training, certification, and practice development.
- Promote consistent architecture deliverables, templates, modeling practices, tools, metadata standards, and documentation practices.
- Build stakeholder relationships, communicate recommendations in business and technical terms, facilitate workshops and design sessions, and drive decisions through analysis and architectural expertise.
Benefits
- Retirement plan
- Health and wellbeing benefits
- Dental, vision, and pharmacy coverage
- Health savings account
- Flexible spending accounts
- Commuter program
- Employee assistance program
- Life and disability insurance
- Adoption assistance
- Back-up childcare
- Tuition/CFA reimbursement
- Paid time off, including leave of absence, paid holidays, volunteer, sick, and vacation time
- Eligible employees may receive a discretionary Corporate Bonus and/or incentives
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What This Job Offers
Job Type
Full-time
Career Level
Senior
