Enterprise Architect, Data

10500 WMC Wellington Management Company LLP; Boston (MA); Hybrid; USD 120,000 - 225,000; Full time

Benefits offered by this job

Retirement plan

Health and wellbeing benefits

Dental coverage

Vision coverage

Flexible spending accounts

Commuter program

Job summary

Wellington Management is seeking an Enterprise Data Architect to shape the firm’s data architecture direction and platform strategy. You will lead data modeling standards, governance, and analytics enablement, partnering with CIOs, product owners, and data governance teams to ensure trusted data and scalable analytics across the enterprise.

The role emphasizes strategic leadership with practical solution delivery, spanning data platforms, AI-enabled data services, and cost-conscious

Qualifications

• Bachelor's degree in technology, CS, data science, engineering, information systems, business.
• 10+ years in technology leadership, enterprise/data/solution architecture roles.
• Experience shaping data strategy, governance, and analytics platforms.
• Strong executive communication with senior stakeholders.

Responsibilities

• Develop data architecture strategies and roadmaps aligned with business priorities.
• Define enterprise data reference architectures, standards, and modeling patterns.
• Partner with data platforms, analytics teams, and governance functions.
• Lead architecture governance, risk management, and evaluations of new tech.
• Influence across stakeholders to balance speed, cost, and quality.

Skills

Executive communication

Data architecture

Enterprise architecture

Architecture leadership

Cloud data architecture

Education

Bachelor's degree in technology / CS / data / engineering / information systems

Tools

TOGAF

DAMA/DMBOK concepts

Job description

About Us

Wellington Management offers comprehensive investment management capabilities that span nearly all segments of the global capital markets. Our investment solutions, tailored to the unique return and risk objectives of institutional clients in more than 60 countries, draw on a robust body of proprietary research and a collaborative culture that encourages independent thought and healthy debate. As a private partnership, we believe our ownership structure fosters a long‑term view that aligns our perspectives with those of our clients.

About the Role

ENTERPRISE Data Architect, TECHNOLOGY wellington management Wellington Management offers comprehensive investment management capabilities that span nearly all segments of the global capital markets. Our investment solutions, tailored to the unique return and risk objectives of institutional clients in more than 60 countries, draw on a robust body of proprietary research and a collaborative culture that encourages independent thought and healthy debate. As a private partnership, we believe our ownership structure fosters a long‑term view that aligns our perspectives with those of our clients.

Tracing our roots to 1928, Wellington Management is one of the world’s largest independent investment management firms. With over US$1 trillion in assets under management as of 30 September 2025, we serve as a trusted adviser to institutional clients and mutual fund sponsors in over 60 countries.

As an Equal Opportunity Employer, we welcome people with diverse life experiences, fresh ideas, and specialized subject‑matter expertise.

The Position

The Enterprise Data Architect will play a senior role in Wellington Management's Enterprise Architecture practice, helping shape the firm's data architecture direction, data platform strategy, analytics architecture, data modeling standards, and AI‑enabling data capabilities. This role is an Enterprise Architect role with a targeted focus on data, responsible for developing architecture strategies, roadmaps, reference architectures, patterns, standards, and technology guidance that enable trusted data, scalable analytics, responsible AI, reduced complexity, managed technology risk, and optimized cost across the enterprise. The person in this role will work directly with Technology Platform CIOs, the head of enterprise data, data product owners, solution architects, architecture domain working groups, data governance partners, and governance teams to ensure that business and technology decisions are outcome‑driven, capability‑first, platform‑centric, and aligned with Wellington's enterprise architecture principles. The role requires a balance of strategic architecture leadership and practical solution engagement, with primary emphasis on enterprise‑level data direction, standards, reuse, governance, risk management, and long‑term platform evolution. The Enterprise Data Architect earns influence through credibility, judgment, collaboration, and demonstrated outcomes. They must be able to translate complex data and AI architecture strategy into clear guidance for senior stakeholders, platform leaders, product teams, data engineering teams, analytics teams, and architecture communities, while helping teams make better decisions that balance speed, cost, resiliency, security, data quality, responsible AI, and risk.

Key Responsibilities

1. Enterprise Data Architecture Strategy and Roadmaps: Develop and maintain data architecture strategies and roadmaps for assigned platforms, domains, and enterprise capabilities, ensuring alignment with Wellington's broader technology, data, AI, and business priorities. Translate business outcomes and analytics objectives into practical data architecture direction, target‑state designs, transition plans, and sequencing recommendations. Partner with data platform leaders, product owners, business analytics teams, and enterprise architects to define capability‑based roadmaps that prioritize business value, governed data access, and trusted data reuse before technology selection. Identify enterprise synergies, dependencies, architectural constraints, and opportunities for simplification across data platforms, analytical environments, integration patterns, reporting capabilities, and AI‑enabling data services. Provide strategic guidance for major data and analytics initiatives, including data platforms, data products, semantic layers, business intelligence, data modeling, responsible AI, agentic systems, metadata, lineage, and data governance. Create clear, consumable architecture communications that help senior leaders and delivery teams understand data architecture tradeoffs, risks, cost implications, and decisions.
2. Data Reference Architectures, Standards, and Modeling Patterns: Define and maintain enterprise data reference architectures, data modeling standards, data architecture patterns, principles, and reusable design guidance that enable consistent, scalable, secure, and resilient data delivery. Promote governed data products, strategic data platforms, reusable data services, common semantic models, and consistent integration patterns across the enterprise. Ensure solutions are designed using approved architecture principles, including everything‑as‑a‑service, everything‑as‑code, security by design, testability, observability, resiliency, strategic data usage, event‑driven architecture, and responsible AI. Establish practical guidance for conceptual, logical, physical, dimensional, domain, and semantic data modeling approaches that support analytical, operational, and AI use cases. Work with domain working groups across data, security, infrastructure, developer experience, and AI to create practical standards and patterns that support business execution and improve data consistency and reuse. Contribute data architecture strategies, standards, patterns, models, metadata, reference architectures, and governance decisions to the central architecture repository, so they are discoverable and reusable.
3. Data Platform, Analytics, and AI Architecture Partnership: Work directly with data platform leaders, business analytics teams, Architecture CIOs, product owners, technology leads, and solution architects to shape data platform roadmaps and product architecture runways. Provide architecture guidance for data platforms, data products, AI platforms, business intelligence and analytics platforms, API platforms, event platforms, semantic layers, data access services, and cloud‑based data infrastructure. Help product and analytics teams move from business demand to approved architecture by connecting requirements, data standards, modeling patterns, platform capabilities, governance, and delivery execution. Bridge enterprise strategy and product delivery by helping teams understand where to reuse existing data capabilities, where to simplify designs, and where custom data engineering creates competitive advantage. Support solution architects, data engineers, analytics engineers, and technical leads with guidance on solution design, non‑functional requirements, integration patterns, cloud‑native practices, data architecture, data modeling, and architecture documentation. Identify opportunities to reduce duplication, retire redundant data technologies, improve reuse, strengthen data quality, and align product‑level data decisions with enterprise architecture direction.
4. Data Governance, Architecture Governance, and Technology Risk Management: Participate in and support the Architecture Review Board and related governance processes to ensure significant data, analytics, and AI technology decisions are reviewed, documented, and aligned with enterprise standards. Assess data architecture risks, model design gaps, data quality risks, metadata and lineage gaps, technology debt, resiliency concerns, integration dependencies, privacy considerations, and security requirements across platforms and major initiatives. Help teams prepare architecture reviews by clarifying decision points, documenting tradeoffs, and ensuring that recommendations are grounded in business outcomes, data governance expectations, and architecture principles. Provide governance oversight without creating unnecessary friction, helping teams move faster through clearer standards, better decision rights, reusable data patterns, and earlier risk identification.
5. Technology Evaluation, Innovation, and Industry Research: Lead or contribute to technology evaluations, proofs of concept, prototypes, and industry research that inform data architecture direction and investment decisions. Assess emerging data, analytics, and AI technologies against Wellington's architecture principles, business capabilities, platform strategy, operational requirements, data governance expectations, and risk posture. Provide structured recommendations on build‑vs‑buy decisions, data platform selection, analytics modernization, semantic‑layer strategies, AI‑enabling data 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. Help establish architecture guidance for strategic areas such as data products, business analytics, AI enablement, agentic systems, integration modernization, cloud data infrastructure, and responsible AI. Communicate evaluation findings in a clear and decision‑oriented manner for senior stakeholders, platform leaders, analytics stakeholders, and implementation teams.
6. Architecture Community, Coaching, and Practice Development: Help build and mature Wellington's architecture community by mentoring solution architects, data architects, data engineers, analytics engineers, technology leads, and engineers on architecture methods, data modeling, standards, and governance expectations. Contribute to architecture training, certification, and practice development efforts, including data architecture, data modeling, architecture governance, roadmaps, patterns, standards, risk, AI architecture, and executive communication. Promote consistent architecture deliverables, templates, modeling practices, tools, metadata standards, and documentation practices across the enterprise. Support architecture domain working groups by bringing enterprise context, cross‑platform data visibility, and practical decision‑making discipline.
7. Stakeholder Engagement and Technical Leadership: Build strong relationships with Product Owners, delivery teams, platform leaders, and business stakeholders. Communicate architecture recommendations in clear business and technical terms. Drive decision‑making through facts, analysis, and architectural expertise rather than authority alone. Facilitate architecture workshops, design sessions, and technical planning discussions. Mentor engineers and emerging architects in architecture methods, design patterns, and technology best practices.

Qualifications

Bachelor's degree in Technology, Computer Science, Data Science, Engineering, Information Systems, Business, or related field; advanced degree or equivalent experience preferred.

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, data 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 through the lenses of business value, trusted data, governance, risk, resiliency, security, cost, operational impact, responsible AI, and long‑term maintainability.

Proven 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, with the ability to translate complex data, analytics, and AI architecture concepts into concise business‑aligned recommendations.

Experience with architecture governance processes, architecture review boards, technology standard, non‑functional requirements, data governance, technical debt management, post‑implementation validation.

Ability to influence without relying solely on formal authority, building trust through expertise, collaboration, follow‑through, and practical judgment.

Familiarity with architecture frameworks, modeling approaches, TOGAF, Open Group standards, DAMA/DMBOK concepts, or related industry architecture and data management practices is preferred.

Demonstrated ability to bring structure and clarity to ambiguous problems while maintaining momentum across multiple stakeholders and initiatives.

Success Profile

A successful Enterprise Data Architect at Wellington Management will be a strategic thinker and practical collaborator who can connect enterprise direction to data, analytics, product, and AI execution.

Job Title

Enterprise Architect, Data

Job Family

InvesTech

Location

280 Congress

Disability Accommodation

If you are a candidate with a disability, or are assisting a candidate with a disability, and require an accommodation to apply for one of our jobs, please email us at [e-mail].

Compensation

At Wellington Management, our approach to compensation is designed to help us attract, inspire and retain the best talent in our industry. We strive to pay employees fairly and competitively across all levels and roles. Our approach to compensation considers all aspects of total compensation; all employees are eligible to receive salary, variable compensation, and benefits. The base salary range for this position is: USD 120,000 – 225,000. This range takes into account the wide range of factors that are considered when making compensation decisions, including but not limited to skill sets; role; skills and experience; certifications; and education. This range is an estimate, and further details on salary and total compensation aspects will be shared with candidates during the recruitment process. Base salary is only one component of Wellington’s total compensation approach. Other rewards may include a discretionary Corporate Bonus and/ or Incentives, if eligible. In addition, we offer a comprehensive and high‑value benefit package to meet the unique needs of our employees and their families, and we are committed to fostering a flexible work environment that enables employees to thrive personally and professionally. Examples of our benefits include retirement plan, health and wellbeing, dental, vision, and pharmacy coverage, health savings account, flexible spending accounts and commuter program, employee assistance program, life and disability insurance, adoption assistance, back‑up childcare, tuition/CFA reimbursement and paid time off (leave of absence, paid holidays, volunteer, sick and vacation time). We believe that in person interactions inspire and energize our community and are essential to our culture. In support of this commitment, our employees work from our offices 4 days a week with flexibility to work remotely 1 day a week.

Company Vision

Tracing our history to 1928, Wellington Management is one of the world’s largest independent investment management firms. We serve as a trusted adviser to clients in over 60 countries, visit our website to see our assets under management. Our innovative investment solutions are built on the strength of proprietary, independent research and span nearly all segments of the global capital markets, including equity, fixed income, multi‑asset, and alternative strategies. As a private partnership whose sole business is investment management, our long‑term views and interests are aligned with those of our clients. We are committed to attracting a talented and diverse workforce, and to fostering an open, collaborative culture of inclusivity because we believe multiple perspectives lead to more informed investment and business decisions. As an Equal Opportunity Employer, we welcome people with diverse life experiences, fresh ideas, and specialized subject‑matter expertise. We believe that in person interactions inspire and energize our community and are essential to our culture. In support of this commitment, our employees work from our offices 4 days a week with flexibility to work remotely 1 day a week. We believe that this approach ultimately supports our mission to deliver investment excellence to our clients and their beneficiaries over the long term.

More Information

For more information, please visit https://www.wellington.com/en/.