- Location
- US - GA - Atlanta, United States of America
- Type
- Full-time
- Department
- Engineering
- Seniority
- Senior
- Experience
- 12+ years
- Visa
- Not sponsored
- Closing date
- Today
- Source
- Workday
Description
Job Description Summary:
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: Practical experience building agentic workflows for engineering productivity, including pipeline generation, test generation, documentation automation, and observability automation.
Modern Data Platforms: Deep understanding of Microsoft Fabric (OneLake, Lakehouses, Warehouses) or equivalent modern Lakehouse architectures (Databricks/Delta Lake).
Programming Languages: Strong proficiency in programming languages relevant to modern data/infrastructure engineering (e.g., Scala, TypeScript).
Skills:
Architecture Strategy, Big Data, Big Data Architecture, Data Lakehouse Architecture, Enterprise Data, Executive Communications, Ontology Engineering, Stream ProcessingPay Range:
United States of America: 217,400 USD - 245,300 USDBase pay offered may vary depending on geography, job-related knowledge, skills, and experience. A full range of medical, financial, and/or other benefits, dependent on the position, is offered.
Annual Incentive Reference Value Percentage:
50Annual Incentive reference value is a market-based competitive value for your role. It falls in the middle of the range for your role, indicating performance at target.
Long-term Incentive Reference Value Percentage:
20Long-term Incentive reference value is a market-based competitive value for your role.
Location(s):
United States of AmericaCity/Cities:
AtlantaTravel Required:
00% - 25%Relocation Provided:
YesJob Posting End Date:
August 14, 2026Our Purpose and Growth Culture:
We are taking deliberate action to nurture an inclusive culture that is grounded in our company purpose, to refresh the world and make a difference. We act with a growth mindset, take an expansive approach to what’s possible and believe in continuous learning to improve our business and ourselves. We focus on four key behaviors – curious, empowered, inclusive and agile – and value how we work as much as what we achieve. We believe that our culture is one of the reasons our company continues to thrive after 130+ years. Visit Our Purpose and Vision to learn more about these behaviors and how you can bring them to life in your next role at Coca-Cola.
We are an Equal Opportunity Employer and do not discriminate against any employee or applicant for employment because of race, color, sex, age, national origin, religion, sexual orientation, gender identity and/or expression, status as a veteran, and basis of disability or any other federal, state or local protected class. When we collect your personal information as part of a job application or offer of employment, we do so in accordance with industry standards and best practices and in compliance with applicable privacy laws.
