Enterprise Architect, Data

Wellington Management•Boston, MA

10d•Hybrid

About The Position

The Enterprise Data Architect is a senior member of Wellington Management's Enterprise Architecture practice, focused on shaping the firm's data architecture direction, data platform strategy, analytics architecture, data modeling standards, and AI-enabling data capabilities. The role develops enterprise strategies, roadmaps, reference architectures, patterns, standards, and technology guidance to enable trusted data, scalable analytics, responsible AI, reduced complexity, managed technology risk, and optimized cost. 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 data direction, standards, reuse, governance, risk management, and long-term platform evolution. It requires translating complex data and AI architecture strategy into clear guidance for senior stakeholders and delivery teams, while balancing speed, cost, resiliency, security, data quality, responsible AI, and risk. Wellington Management is an independent investment management firm with roots dating to 1928. It serves institutional clients and mutual fund sponsors in more than 60 countries and reported over US$1 trillion in assets under management as of September 30, 2025. The position is listed in the InvesTech job family at 280 Congress. The role is part of a flexible work environment in which employees work from the office four days per week and may work remotely one day per week.

Requirements

Bachelor's degree in Technology, Computer Science, Data Science, Engineering, Information Systems, Business, or a related field; equivalent experience is also referenced as preferred in lieu of an advanced degree.
At least 10 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, building trust through 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, modeling approaches, TOGAF, Open Group standards, DAMA/DMBOK concepts, or related industry architecture and data management practices.

Responsibilities

Develop and maintain data architecture strategies and roadmaps for platforms, domains, and enterprise capabilities, aligned with technology, data, AI, and business priorities.
Translate business outcomes and analytics objectives into data architecture direction, target-state designs, transition plans, and sequencing recommendations.
Partner with platform leaders, product owners, analytics teams, and enterprise architects to define capability-based roadmaps prioritizing business value, governed access, and trusted data reuse.
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.
Communicate architecture tradeoffs, risks, cost implications, and decisions to senior leaders and delivery teams.
Define and maintain enterprise data reference architectures, modeling standards, architecture patterns, principles, and reusable design guidance.
Promote governed data products, strategic platforms, reusable services, common semantic models, consistent integration patterns, and standard analytics architectures.
Apply approved principles such as everything-as-a-service, everything-as-code, security by design, testability, observability, resiliency, strategic data usage, event-driven architecture, and responsible AI.
Establish guidance for conceptual, logical, physical, dimensional, domain, and semantic data modeling.
Collaborate with data, security, infrastructure, developer experience, and AI working groups to develop practical standards and patterns.
Contribute data strategies, standards, patterns, models, metadata, reference architectures, and governance decisions to the central architecture repository.
Work with platform leaders, analytics teams, CIOs, product owners, technology leads, and solution architects to shape platform roadmaps and product architecture runways.
Provide architecture guidance for data, AI, business intelligence and analytics, API, and event platforms; semantic layers; data access services; and cloud data infrastructure.
Help product and analytics teams connect requirements, standards, modeling patterns, platform capabilities, governance, and delivery execution.
Guide teams on reuse, simplification, and where custom data engineering can create competitive advantage.
Support solution architects, data engineers, analytics engineers, and technical leads with solution design, non-functional requirements, integration patterns, cloud-native practices, data architecture, modeling, and documentation.
Identify opportunities to reduce duplication, retire redundant technologies, improve reuse and data quality, and align product-level decisions with enterprise architecture direction.
Participate in the Architecture Review Board and related governance processes, reviewing and documenting significant data, analytics, and AI technology decisions.
Assess architecture risks and gaps involving data models, data quality, metadata, lineage, technology debt, resiliency, integration, privacy, and security.
Help teams prepare architecture reviews by clarifying decision points and documenting tradeoffs grounded in business outcomes, governance expectations, and architecture principles.
Support effective governance through clear standards, decision rights, reusable patterns, and early risk identification without unnecessary friction.
Support post-implementation architecture reviews and validation against approved direction and non-functional requirements.
Partner with technology risk, information security, infrastructure, data governance, privacy, and AI governance teams on control, compliance, resilience, responsible AI, and operational expectations.
Lead or contribute to technology evaluations, proofs of concept, prototypes, and industry research to inform data architecture and investment decisions.
Assess emerging data, analytics, and AI technologies against architecture principles, business capabilities, platform strategy, operational requirements, governance, and risk posture.
Provide recommendations on build-versus-buy decisions, platform selection, analytics modernization, semantic-layer strategies, AI-enabling services, and technology lifecycle considerations.
Evaluate technologies for scalability, resiliency, security, observability, maintainability, cost, developer experience, data quality, metadata, lineage, governance fit, and enterprise alignment.
Establish architecture guidance for data products, business analytics, AI enablement, agentic systems, integration modernization, cloud data infrastructure, and responsible AI.
Communicate evaluation findings clearly and in a decision-oriented manner to senior stakeholders, platform leaders, analytics stakeholders, and implementation teams.
Mentor solution architects, data architects, data engineers, analytics engineers, technology leads, and engineers on architecture methods, data modeling, standards, and governance.
Contribute to architecture training, certification, and practice development in data architecture, modeling, governance, roadmaps, patterns, standards, risk, AI architecture, and executive communication.
Promote consistent architecture deliverables, templates, modeling practices, tools, metadata standards, and documentation practices.
Support architecture domain working groups with enterprise context, cross-platform data visibility, and practical decision-making discipline.
Foster collaboration among enterprise and solution architects, data platform and analytics teams, product teams, and platform leaders.
Build relationships with product owners, delivery teams, platform leaders, and business stakeholders; communicate recommendations in business and technical terms.
Drive decisions through facts, analysis, and architectural expertise; facilitate architecture workshops, design sessions, and technical planning discussions.
Mentor engineers and emerging architects and act as a trusted advisor on complex technical decisions and competing priorities.

Benefits

Retirement plan
Health and wellbeing coverage
Dental coverage
Vision coverage
Pharmacy coverage
Health savings account
Flexible spending accounts
Commuter program
Employee assistance program
Life insurance
Disability insurance
Adoption assistance
Back-up childcare
Tuition/CFA reimbursement
Paid time off, including leave of absence, paid holidays, volunteer, sick, and vacation time
Discretionary Corporate Bonus and/or incentives, if eligible
Comprehensive benefits package for employees and their families