Senior Director, Data Architecture (Next Gen)

Coca-Cola; United States; On-site; USD 180,000 - 260,000; Full time

Job summary

Coca-Cola is hiring a Senior Director of Next-Gen Data Architecture to lead the evolution of our global data ecosystem. You and your team will serve as the Data Architecture CoE, enabling data engineers, platform engineers, and analysts to build robust, scalable data solutions for enterprise-scale needs.

The role requires strategic leadership with deep technical expertise in data architectures, governance, and advanced analytics, while maintaining hands-on delivery and collaboration with

Qualifications

• Seasoned data architecture leader with CoE experience.
• Proven ability to translate business needs into scalable data platforms.
• Strong executive stakeholder communication and governance skills.

Responsibilities

• Lead the Data Architecture CoE and set architectural standards.
• Mentor senior data architects and engineers across teams.
• Design modern data platforms for enterprise-scale needs.
• Develop knowledge graphs, ontologies, and semantic models.
• Drive AI-driven data engineering workflows and API strategies.
• Oversee streaming and real-time data platform initiatives.

Skills

Data governance

Executive communication

Leadership

Architectural leadership

Stream processing

Education

Master's degree in CS/Engineering

Tools

Kafka

Azure AKS

Graph databases

Jena/Palantir/Stardog

Job description

As Senior Director of Next-Gen Data Architecture, you will lead the evolution of our global data ecosystem and help shape the foundation for the next generation of intelligent enterprise computing. In this role, you and your team will act as the Data Architecture Center of Excellence (CoE), empowering and enabling data engineers, platform engineers, and analysts across the enterprise to build robust, future-proof data solutions.You will be responsible for modernizing data platforms, establishing scalable architecture standards, and turning complex business requirements into practical, high-impact solutions. Leading a specialized team of key data architects, this position combines strategic leadership with technical depth, requiring someone who can guide architectural direction while remaining closely connected to implementation and delivery.The ideal candidate is equally comfortable working with executive stakeholders, engineering leaders, and development teams. You will build, manage, and mentor a high-performing organization while helping define the frameworks, platforms, and best practices that support enterprise-scale data initiatives.

Core Responsibilities

• Center of Excellence Enablement: Act as the strategic and technical CoE, providing architectural guidance, reference architectures, and ongoing support to enable data engineers, platform engineers, and analysts.
• Team Leadership & Mentorship: Direct, mentor, and develop a team of key data architects, fostering a culture of technical excellence, collaboration, and continuous innovation.
• Next-Generation Data Architecture: Lead the design and implementation of modern data platforms and engineering frameworks that support large-scale business and operational needs, including complex supply chain, manufacturing, retail, and execution systems.
• Knowledge Graphs & Ontologies: Drive the development of graph-based data solutions and semantic models that improve data connectivity, business context, and cross-functional insights across the enterprise.
• AI-Driven Data Engineering: Identify and implement opportunities to leverage AI and automation throughout the data engineering lifecycle, from design and development through operations and optimization.
• API and Knowledge Layer Strategy: Define scalable API and knowledge-layer architectures that enable consistent access to trusted data and support both operational and analytical workloads.
• Streaming and Real-Time Data Platforms: Build and enhance real-time data capabilities that support event-driven processing, operational intelligence, and responsive business applications.
• Developer Productivity: Improve engineering efficiency through modern tooling, automation, and platform capabilities. Champion practices that simplify development, strengthen governance, and accelerate delivery while maintaining enterprise standards.

Required Qualifications & Experience

Leadership, Strategy & Domain Experience

• 12+ years of experience in data engineering, architecture, and advanced analytics, with at least 5+ years in a senior leadership capacity.
• Architect Leadership: Proven track record of hiring, managing, and mentoring senior technical talent, specifically Enterprise Data Architects, Principal Engineers, or Engineering Managers.
• CoE & Governance: Prior experience operating within or leading a Center of Excellence (CoE) or enterprise-wide foundational architecture team, with a strong understanding of enterprise architecture governance and enablement.
• Executive Communication: Ability to translate complex technical concepts into business value for executive stakeholders, while effectively evangelizing architectural standards across diverse engineering teams.

Core Engineering & Automation

• Kappa & Stream Processing: Deep architectural understanding and hands‑on experience building stream‑only architectures (Kappa). Advanced proficiency with streaming technologies such as Apache Kafka, Azure Event Hubs, Spark Structured Streaming (or Flink).
• Context & Ontology Engineering: Proven experience designing enterprise ontologies, taxonomies, and managing semantic context layers. Experience with Jena/Palantir/Stardog ecosystem capabilities, or comparable semantic/graph platforms is a plus.
• Graph Databases: Hands‑on experience with Graph ecosystems (e.g., Neo4j, Azure Cosmos DB Graph API, or similar Graph/Vector databases) and graph query languages.
• Advanced Developer Tooling: Deep familiarity with integrating and customizing automated development tools (e.g., GitHub Copilot, Codex, etc.).
• Testing & Evaluation Frameworks: Experience building automated testing frameworks or benchmarking harnesses specifically designed to evaluate automated outputs, agentic workflows, and complex data pipelines.
• API & Container Deployment: Hands‑on experience developing data APIs (REST, GraphQL, or gRPC) and deploying them at enterprise scale using Docker and Azure Kubernetes Service (AKS).
• AI-Driven Workflows: Pra