Data Engineer

Data Engineer

Team: OU Digital, Japan & South Korea Operating Unit

Reports To: Senior Director, Data & Analytics

The Coca-Cola Company (TCCC) is evolving into a more digital-first, data-driven enterprise to fuel sustainable growth, increase speed to market, and unlock new sources of value. Rapid advances in technology, data, and AI create a unique opportunity to accelerate The Coca-Cola Company system's next chapter of growth by reimagining our core competitive advantages. Building on a strong foundation of modernized infrastructure, global digital experiences, early data capabilities, and proven use cases, we are now shifting from early wins to scaled, end-to-end impact on growth, productivity, and efficiency.

This next phase moves us from an analog world to a fully digitized one, powered by a digital growth engine that embeds data, technology, and AI into our most critical business domains. Success will require more than technology implementation - it demands a strategic transformation of core capabilities, a domain-based, product-centric operating model, and a cultural shift toward experimentation, data and technology fluency, and seamless partnership between business and digital teams.

Job Description Summary

The Director, Data Engineering owns the data engineering function for the Japan & South Korea Operating Unit, leading the design, delivery, and operation of enterprise data platforms and pipelines. The role translates data strategy into scalable engineering roadmaps, builds and leads a data engineering team, and represents data engineering in OU data governance forums.

As the engineering leader for JKOU's data foundation, the Director ensures platforms are reliable, automated, and engineered for scale - enabling trusted, high-quality data across the organization's most critical business domains.

Responsibilities include

• Own and lead ETL and data pipeline engineering for OU data products and platforms, setting technical direction and engineering standards.

• Translate the data strategy into scalable engineering roadmaps, technical designs, and multi-year platform plans.

• Design, build, and operate enterprise data platforms in alignment with global architecture standards, ensuring scalability and resilience.

• Automate data pipelines and operations to maximize reliability and minimize manual effort.

• Ensure CI/CD reliability, platform performance, and engineering excellence across the data estate.

• Integrate local and system data sources, including bottler and partner data, into governed platforms.

• Partner with data science, governance, and product management to deliver end-to-end data products.

• Manage vendor engineering resources and partnerships, ensuring quality, cost-effectiveness, and delivery accountability.

• Build, lead, and develop a data engineering team, fostering technical excellence and career growth.

• Represent data engineering in OU data governance forums, advocating for platform standards, data quality, and architectural integrity.

• Owns the engineered data foundation for OU analytics, AI, and data products, directly determining their reliability and scalability.

• Leads a data engineering team and vendor partners, shaping engineering talent and capability for the OU.

• Represents data engineering in governance and architecture forums, influencing OU-wide data standards.

• Sets the technical direction for modern data engineering practices - automation, CI/CD, infrastructure-as-code - to raise platform excellence across the OU.

• Solves complex, ambiguous data integration challenges across system, bottler, and partner sources, often without established precedent.

• Balances near-term delivery pressure with long-term architectural sustainability.

• Communicates engineering strategy, trade-offs, and platform health to senior data and business leadership.

• Coordinates across global platform teams, local stakeholders, and vendors to align priorities and resolve conflicts.

• Represents data engineering in OU governance forums, influencing standards adopted across teams.

• 10+ years of experience in data engineering, including ETL/ELT, data platforms, and pipeline operations, with demonstrated progression into leadership.

• Proven experience building and leading data engineering teams.

• Strong proficiency in modern data stacks (cloud data platforms, orchestration, CI/CD).

• Experience designing scalable data architectures aligned with enterprise standards.

• Experience representing engineering functions in governance or architecture review forums.

• Experience with vendor management and Agile delivery.

• Business-level English required; Japanese proficiency preferred.