Enterprise Architect - Data & Integration

Allegis Group•Hanover, MD

4d•Onsite

About The Position

The Enterprise Architect for Data and Integration is a senior technology leadership role within the Enterprise Architecture practice, responsible for shaping enterprise-wide data and integration architecture strategy in alignment with organizational priorities and long-term technology vision. Operating at the intersection of business strategy and technology execution, this role partners with C-suite and senior IS leadership, supports governance bodies including ESIC, Coalition and Cohort committees, and serves as a key voice in enterprise-level architecture decisions spanning data, integration and information management. As a strategic advisor and thought leader, the Enterprise Architect drives technology investment, portfolio planning and architecture governance — ensuring data and integration decisions are coherent with and contributory to the broader enterprise architecture direction, being accountable for defining the master data and integration strategy. This role is also expected to bring a forward-looking perspective on AI and Generative AI, governing responsible adoption within the value stream and championing AI-enabled ways of working that accelerate architecture productivity and business outcomes. Within the Data and Integration context, this role provides focused architecture leadership across information architecture, integration patterns and data quality — working closely with IS Strategy, IS Delivery, Platform Architects and Allegis Business Partners to define future-state vision, govern data models and integration standards, ensure data quality and validation practices, and maintain architectural integrity across delivery. Required in-office presence at least 5 days per week

Requirements

10+ years of progressive experience in technology architecture roles, with at least 5 years at an Enterprise or Senior Architect level within a large, matrixed organization.
Demonstrated experience designing and governing integration architectures across hybrid and multi-cloud environments, connecting enterprise SaaS, PaaS and on-premise boundary applications at scale.
Proven track record of defining and delivering master data strategies, data-sharing frameworks and canonical data models that support enterprise-wide business needs.
Strong understanding of Snowflake platform architecture including data sharing, data mesh patterns and multi-cluster architecture — with familiarity with Snowflake Cortex for AI-augmented data capabilities as a strong advantage
Familiarity with MuleSoft Anypoint Platform including API-led connectivity, design, deployment and lifecycle management across hybrid and multi-cloud environments spanning Azure, AWS and Google Cloud
Experience designing or enabling enterprise solutions using Generative AI and agentic AI design patterns — including MCP patterns for agentic AI integration and Snowflake Cortex — across Azure, AWS and Google Cloud incorporating security considerations and responsible AI guardrails
Strong history of engaging and influencing C-suite, senior IS leadership and business stakeholders, translating complex architecture concepts into clear strategic recommendations
Experience supporting and enabling enterprise governance bodies, leadership committees and cross-functional architecture communities of practice
Experience operating within SAFe or scaled agile delivery models, including PI planning, Architecture Review Boards and squad-based delivery, embedding architecture direction within iterative delivery rhythms
Demonstrated hands‑on use of AI productivity tools (e.g., Microsoft Copilot or equivalent) to improve day‑to‑day effectiveness—such as accelerating analysis, architecture design, documentation, and decision support—and to model AI‑enabled ways of working.
Bachelor's degree in Computer Science, Information Systems or a related field; advanced degree or architecture certifications (TOGAF, AWS, Azure, MuleSoft) preferred.
Data & Integration Architecture: Strong command of enterprise data architecture, integration design patterns and information architecture principles — including data mesh, event-driven architecture, API-led connectivity and cloud-native integration
Snowflake & Data Platform: Proficiency in Snowflake architecture including data sharing, data mesh, multi-cluster design and Cortex AI capabilities — with broader familiarity across modern data platform ecosystems including ingestion, transformation and consumption layers
MuleSoft & Integration Platforms: Proficiency in MuleSoft Anypoint Platform, API gateway patterns, AsyncAPI and REST standards — with working knowledge of iPaaS, middleware and enterprise service bus patterns across hybrid environments
Multi-Cloud & SaaS Integration: Working knowledge of hybrid and multi-cloud integration architecture across Azure, AWS and Google Cloud — including Salesforce, Oracle Fusion SaaS/PaaS and boundary application connectivity
API & Event-Driven Architecture: Deep knowledge of API design standards (REST, GraphQL, AsyncAPI), API gateway patterns, event-driven architecture (EDA), messaging platforms and MCP (Model Context Protocol) patterns for AI-agent and enterprise integration use cases
Enterprise AI & GenAI Architecture: Knowledge of Generative AI and agentic AI design patterns across cloud platforms including Microsoft Azure AI, AWS and Google Cloud — including responsible AI guardrails, security considerations and integration of AI capabilities into existing enterprise architectures
Master Data Management: Experience defining and governing MDM strategies, canonical data models, data domains and data-sharing frameworks at enterprise scale
Data Governance & Quality: Familiarity with data governance frameworks, data quality tooling, data profiling, metadata management and data lineage practices
Architecture Frameworks & Modeling: Proficiency in TOGAF, Zachman and architecture modeling tools such as ArchiMate, Sparx EA or LeanIX — with strong command of data modeling (conceptual, logical, physical), process modeling and object modeling techniques
Agile & SAFe Practices: Experience operating within SAFe or scaled agile delivery models, including PI planning, Architecture Review Boards and squad-based delivery
Stakeholder Engagement & Communication: Exceptional ability to engage, influence and enable leaders across C-suite, Coalition, Cohort and ESIC — translating complex architecture concepts into clear, actionable guidance for both technical and non-technical audiences
Architecture Governance & Standards: Demonstrated ability to define and enforce architecture principles, NFRs, modeling standards and review processes — ensuring design consistency, compliance and architectural integrity across value stream delivery
Architecture Community & Talent Development: Experience leading communities of practice, mentoring Solution and Domain Architects and shaping engineering culture through sound design thinking, knowledge sharing and continuous improvement practices
Build relationships
Develop people
Lead change
Inspire Others
Think critically
Communicate clearly
Create Accountability

Nice To Haves

Familiarity with staffing, talent acquisition, workforce solutions or professional services industry technology ecosystems is a strong advantage.

Responsibilities

Architecture Vision & Roadmap: Develops and maintains enterprise data and integration technology roadmaps aligned to organizational priorities, defining future-state information architecture vision, capability frameworks and baseline assessments in partnership with the Delivery Manager, Enterprise Architecture.
Business-Technology Alignment: Partners with IS Delivery, IS Strategy, Coalition Leadership and Allegis Business Partners to translate business priorities into data and integration architecture direction, ensuring technology investments deliver measurable outcomes and align with organizational initiatives across ESIC.
Stakeholder Engagement & Enablement: Engages and enables leaders across Coalition, Cohort and ESIC broadly, serving as a trusted architecture advisor who bridges data and integration strategy with execution and ensures alignment across organizational boundaries.
Market & Technology Intelligence: Reviews market trends across data management, integration platforms, API ecosystems and emerging technologies — recommending strategies for new technology adoption and conducting assessments and vetting for new investments aligned to industry patterns such as data mesh, event-driven architecture and cloud-native integration.
Design Authority & Solution Guidance: Serves as the design authority for enterprise data and integration architecture, providing guidance on solution decisions across master data management, data sharing, API design and integration patterns, and acting as the escalation path for cross-domain architecture conflicts.
Standards & Modeling Governance: Determines and maintains overall standards, guidelines and best practices for data modeling, process modeling, object modeling and integration design — enforcing data validation, quality rules and profiling standards to ensure consistency and integrity across the enterprise.
Artificial Intelligence & GenAI Leadership: Evaluates emerging AI and Generative AI patterns, governs responsible adoption within the value stream, and models AI-enabled ways of working — leveraging tools such as Microsoft Copilot and platform-native AI capabilities to accelerate architecture productivity and deliver business outcomes across the enterprise.
Architecture Review & Compliance: Reviews enterprise technical designs to ensure alignment with defined architecture principles, data standards, non-functional requirements (NFRs) and integration guardrails, using data quality and profiling tools to detect and address variations from established standards.
Master Data & Integration Strategy: Defines and governs the master data and integration strategy, enabling the creation of master data stores, data-sharing frameworks and integration processes that leverage canonical data models to meet enterprise business needs.
Platform & Domain Collaboration: Liaises with Enterprise, Solution and Domain Architects to share best practices and insights, bridging platform capabilities — including middleware, iPaaS, API gateways and data platforms — into actionable, domain-specific architecture guidance.
Risk & Technical Debt Management: Identifies and communicates data quality risks, integration debt and systemic constraints early in the delivery lifecycle to inform prioritization, investment decisions and portfolio planning.
Agile Delivery Enablement: Participates in PI planning, Architecture Review Boards and squad ceremonies to embed data and integration architecture direction within agile delivery rhythms and support iterative solution development.
Architecture Community & Talent Development: Leads the architecture community of practice, coaches and mentors Solution and Domain Architects, and shapes engineering culture by championing sound data management principles, integration design thinking and continuous improvement practices.

Benefits

Medical, dental & vision
Hospital plans
401(k) Retirement Plan – Pre-tax and Roth post-tax contributions available
Life Insurance (Company paid Basic Life and AD&D as well as voluntary Life & AD&D for the employee and dependents)
Company paid Short and long-term disability
Health & Dependent Care Spending Accounts (HSA & DCFSA)
Transportation benefits
Employee Assistance Program
Tuition Assistance
Time Off/Leave (PTO, Allegis Group Paid Family Leave, Parental Leave)