Chief Data Architect

Role Summary

The Chief Data Architect is responsible for defining and governing the enterprise‑wide data architecture strategy to support business growth, digital transformation, analytics, AI, and regulatory requirements. This role serves as the technical authority and strategic partner to executive leadership, ensuring data platforms, integration patterns, and governance frameworks enable scalable, trusted, and value‑driven data use across the organization.

Key Responsibilities

Enterprise Data Strategy & Architecture

• Define and own the enterprise data architecture vision, principles, and target‑state roadmap aligned to business strategy.
• Establish standards for data platforms, integration, storage, analytics, and AI enablement.
• Ensure architectural decisions balance scalability, cost, security, and agility.

Business & Executive Partnership

• Partner with C‑suite, business leaders, and domain owners to translate strategic priorities into data architecture capabilities.
• Advise leadership on data investment decisions, trade‑offs, and long‑term implications.
• Act as a trusted authority on how data architecture enables revenue, efficiency, and risk reduction.

Data Platform & Modernization Oversight

• Guide design and evolution of cloud/on‑prem/hybrid data platforms.
• Define patterns for ingestion, transformation, analytics, ML/AI, and data sharing.
• Ensure platforms are production‑ready, resilient, and cost‑optimized.

Governance, Trust & Risk Management

• Architect enterprise approaches to data governance, quality, lineage, metadata, privacy, and security.
• Ensure compliance with regulatory and industry requirements.
• Champion trusted, auditable data as a foundational enterprise asset.

Operating Model & Enablement

• Define the data architecture operating model, including decision rights, standards, and engagement with delivery teams.
• Provide architectural guidance and guardrails without slowing delivery.
• Mentor senior architects and elevate data architecture maturity across teams.

Success Measures

• Clear, adopted enterprise data architecture roadmap
• Improved speed and consistency of data delivery across domains
• Reduced architectural fragmentation and technical debt
• Increased confidence in data quality, lineage, and governance
• Data platforms that reliably support analytics, AI, and scale

Required Experience & Qualifications

Experience

• 12+ years in data architecture, with significant experience at enterprise scale
• Proven leadership in data platform strategy, modernization, or transformation
• Experience influencing decisions at executive and board levels
• Hands‑on understanding of analytics, cloud data platforms, and data governance

Technical Depth

• Enterprise data architecture (conceptual, logical, physical)
• Cloud data platforms and modern integration patterns
• Analytics, BI, AI/ML enablement architectures
• Data governance, security, privacy, and compliance
• SDLC and production‑grade data delivery

Leadership & Mindset

• Strategic thinker with strong execution orientation
• Able to influence without direct authority
• Communicates complex concepts clearly to technical and non‑technical audiences
• Pragmatic, outcome‑focused, and business‑driven