Enterprise Architecture Principal - Data & Analytics

The  
** Enterprise*
* ** Architecture Principal - Data & Analytics
** is a senior technology leader responsible for defining the future  
** enterprise data and analytics architecture strategy, target states, and multi-year roadmaps** . This role  
** recognized architecture authority
** architecture strategies, establishes technology standards, and creates multi-year roadmaps that support business goals and setting the  
** northstar vision
** for modern data platforms, analytics, and AI-enabled capabilities-translating business priorities into  
** pragmatic, scalable, and future-ready architectures** . The individual will be operating with high enterprise influence and no direct reports, this role requires strong executive presence, the ability to influence without authority, and a relentless focus on enabling  
** data-driven decision making, hyper-personalization, and AI-first innovation** .

** Key Outcomes*
* +  
** Enterprise Data & Analytics Vision:
** Define and publish a  
** business-aligned data and analytics architecture strategy
** with a clear  
** 3-5 year roadmap
** covering data platforms, governance, analytics, AI/ML, and integration layers.

+  
** Scalable & Reusable Data Foundations:
** Establish  
** modern, modular data architectures
** that reduce fragmentation, promote reuse, and enable enterprise-scale analytics and AI.

+  
** Decision Velocity through Architecture Governance:
** Implement  
** architecture principles, guardrails, and decision frameworks
** to improve speed, consistency, and quality of analytics and data platform decisions.

+  
** AI-Ready & Insights-Driven Enterprise:
** Enable  
** analytics-ready data, semantic layers, and AI capabilities
** that accelerate insights, automation, and intelligent decisioning.

+  
** Cross-Domain Alignment:
** Act as a unifying architecture leader across  
** Digital, Data, AI, Security, and Business domains
** to ensure alignment on key investment and design decisions.

** Responsibilities*
* + Develop and lead enterprise data and analytics architecture strategies and roadmaps.

+ Design and evolve  
** enterprise data & analytics architecture strategy, capability maps, and target-state designs*
* + Develop and maintain  
** multi-year roadmaps
** aligned to business outcomes, cost optimization, and innovation priorities.

+ Lead architecture decisions for large-scale data, analytics, and AI initiatives.

+ Architect and support  
** modern data platforms**  (cloud data lakehouse, streaming, real-time pipelines, semantic/ontology layers).

+ Partner with engineering, product, data, and business teams to deliver scalable and cost-effective solutions.

+ Evaluate emerging technologies and recommend innovative solutions that support business objectives.

+ Enable  
** self-service analytics** , BI, and advanced analytics capabilities across the enterprise.

+ Lead architecture for  
** AI/ML platforms, feature stores, and model lifecycle integration** .

+ Embed  
** data governance, quality, lineage, metadata, and stewardship frameworks
** into architecture design.

+ Drive innovation in  
** AI/ML, GenAI, agentic analytics, and intelligent automation** .

+ Provide architecture leadership for  
** high-impact data and analytics initiatives** .

+ Establish  
** reference architectures, reusable patterns, and standards
** for enterprise adoption.

+ Develop reusable architecture patterns, frameworks, and standards for enterprise adoption.

+ Support modern engineering practices, including Data Ops, MLOps, and automated deployment processes.

+ Partner with engineering, product, and data teams to ensure architectures are  
** executable, scalable, and cost-efficient** .

+ Provide technical leadership, mentoring, and guidance across the architecture and data community.

+ Enable adoption of  
** modern engineering practices**  (Data Ops, MLOps, CI/CD for data).

+ Influence strategic technology decisions and drive alignment across multiple teams and business areas.

+ Serve as a  
** mentor and thought leader
** across the architecture and data community.

+ Drive adoption of  
** best practices, patterns, and architectural discipline** .

** Qualifications*
* + Bachelor's degree in Computer Science, Engineering, or a related field.

+ 10+ years of experience in enterprise architecture, data engineering, analytics platforms, or related disciplines.

+ Strong knowledge of cloud platforms such as Azure, AWS, or Google Cloud Platform (GCP).

+ Proven success defining  
** data/analytics architecture strategies, target states, and roadmaps** .

+

Experience with modern data platforms, APIs, streaming technologies, and data integration patterns.

+ Knowledge of data governance, privacy, security, and compliance frameworks.

+ Deep experience in  
** large-scale, regulated enterprise environments**  (e.g., healthcare, financial services).

+

Experience with artificial intelligence (AI), machine learning (ML), and advanced analytics solutions.

+ Strong ability to  
** influence senior stakeholders without direct authority** .

+ Strong communication,…