Senior Enterprise Data Architect
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Key skills for this role
Role Overview
The role defines and delivers modern, scalable, and governed data architectures across the organization.
The position supports data trust, data-driven decision-making, AI, and advanced analytics at enterprise scale.
The role requires more than 20 years of progressive experience across data architecture, data engineering, technology, AI, analytics, or enterprise architecture.
Key Skills for This Role
Full Job Posting
Role overview
The role defines and delivers modern, scalable, and governed data architectures across the organization.
The position supports data trust, data-driven decision-making, AI, and advanced analytics at enterprise scale.
The role requires more than 20 years of progressive experience across data architecture, data engineering, technology, AI, analytics, or enterprise architecture.
Strategy and architecture
- Define and execute enterprise AI, data, analytics, and information management strategies.
- Develop roadmaps for data architecture, AI adoption, analytics, data governance, and digital transformation.
- Lead the architecture, design, implementation, and management of enterprise data platforms and AI solutions.
- Establish architectures for data lakes, data warehouses, integration platforms, BI environments, ML platforms, and information management systems.
Governance and organizational capability
- Establish enterprise-wide data governance frameworks, policies, standards, and operating models.
- Improve data quality, availability, security, privacy, lineage, ownership, and usability.
- Build capabilities that promote data literacy and responsible AI use.
- Lead the formation, development, and optimization of AI, data, analytics, and architecture teams.
Leadership and delivery
- Advise executive leadership on AI strategy, data investments, technology priorities, and transformation initiatives.
- Translate business objectives into practical data, analytics, and AI solutions.
- Oversee large-scale data and AI programs from strategy and planning through implementation and operations.
- Collaborate with business, technology, risk, security, compliance, and operations stakeholders.
- Define architecture principles, reference models, design standards, and technology governance processes.
- Evaluate emerging AI, data, cloud, and analytics technologies and recommend enterprise solutions.
Compliance and responsible technology
- Ensure AI and data initiatives align with regulatory, security, privacy, and ethical requirements.
- Promote advanced analytics, predictive modeling, machine learning, and intelligent automation.
Required qualifications
- Bachelor's degree in computer engineering, computer science, information systems, data science, or a related discipline.
- Extensive experience in enterprise data architecture, data governance, data management, data warehousing, and business intelligence.
- Proven experience leading enterprise-scale transformation programs.
- Strong background designing and implementing data warehouses, data lakes, data integration solutions, and analytics platforms.
- Experience developing and implementing AI and machine learning strategies.
- Experience establishing data governance and data management operating models.
- Experience leading multidisciplinary teams and building technology or data-focused organizational units.
- Strong understanding of enterprise architecture, software development, systems integration, and information management.
- Experience working with senior executives and translating technical concepts into business outcomes.
Preferred qualifications
- Experience in banking or financial services is strongly preferred.
- Experience in telecommunications, retail, utilities, healthcare, or government is considered valuable.
- A master's degree or professional certifications in enterprise architecture, data management, cloud technology, AI, analytics, or governance is preferred.
- Experience with cloud data platforms, modern data architectures, ML platforms, advanced analytics, responsible AI, AI risk, privacy, cybersecurity, or regulatory compliance is preferred.
- Experience managing large budgets, strategic programs, external partners, enterprise technology portfolios, or regulated environments is preferred.
Core competencies
- Enterprise AI and data strategy; data architecture and information management; data governance and data quality.
- Artificial intelligence and machine learning; data warehousing and data lakes; business intelligence and advanced analytics.
- Data integration and platform modernization; enterprise architecture; organizational design and capability building.
- Executive communication, stakeholder management, strategic planning, roadmap development, and program leadership.
- Innovation, digital transformation, and responsible and ethical AI adoption.
Key performance indicators
Progress against the enterprise AI and data strategy roadmap.
Improvement in data quality, accessibility, governance, and trust.
Successful delivery of AI, analytics, and data platform initiatives.
Increased adoption of data-driven decision-making across business functions.
Improved data literacy and maturity across the organization.
Business value generated through analytics, automation, and AI use cases.
Effectiveness, scalability, and resilience of enterprise data architecture.
Compliance with data protection, security, privacy, and governance requirements.
Successful development and retention of high-performing AI and data teams.
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