Director, Data Engineer

Location

Atlanta, GA (Global HQ)

0-20% (OU, Bottler meetings, industry conferences)

None

The Global Equipment Platforms (GEP) team is seeking a highly skilled and experienced Lead Data Engineer to be a core technical contributor to the data backbone for The Coca-Cola Company's global fleet of 17MM+ connected equipment. Reporting to the Head of Data within GEP Digital, this role is pivotal in transforming raw telemetry data from beverage vending machines, dispensers, coolers, and retail racks into a strategic asset that fuels real-time market insights, predictive analytics, and operational efficiencies across our global ecosystem.

You will be responsible for designing, building, and maintaining robust, secure, and cost-optimized cloud-based data pipelines and platforms, primarily leveraging Microsoft Azure. This includes hands‑on development of scalable data ingestion, transformation, and storage solutions capable of handling high-volume, real-time data from a diverse fleet of equipment running on the KO Operating System (KOS) and other embedded systems. This role demands a deep technical expert with a proven track record of solving complex data challenges, ensuring data integrity, scalability, and accessibility for both internal stakeholders and our 200+ global franchise bottlers and OEM partners in a multi-tenant environment.

• Design, develop, and maintain highly scalable, secure, and resilient data pipelines (batch, streaming, real-time) and data platforms on Microsoft Azure (e.g., Azure Data Factory, Azure Synapse Analytics, Azure Databricks, Event Hubs, IoT Hub, ADLS Gen2, Cosmos DB, Azure SQL).
• Implement robust data ingestion processes to collect high-volume telemetry data from 17MM+ connected devices, ensuring data quality and reliability at source.
• Develop efficient data transformation logic and data models to rationalize, cleanse, and enrich raw equipment data, making it ready for consumption by analytics and AI applications.
• Optimize data storage solutions (data lakes, data warehouses) for performance, cost-efficiency, and accessibility.
• Design and build scalable, resilient data pipelines for real-time telemetry, ensuring data quality and accessibility that directly fuels the analytical models developed by Data Scientists and the production AI systems deployed by the Lead AI Engineer.

• Engineer the data foundation required to support advanced analytics, machine learning models (e.g., predictive maintenance, demand forecasting, personalization), and AI Agents.
• Work closely with Data Scientists and Data Analysts to understand their data needs, ensure data quality, and optimize data structures for efficient model training and inference.
• Develop and maintain curated datasets and data marts that simplify data consumption for business intelligence tools and internal/external analytics applications.
• Ensure the seamless flow of rich, rationalized telemetry data from KOS-powered devices to the core analytics platform.

• Contribute to the implementation and enforcement of data governance frameworks, data quality standards, and data integrity checks for the equipment data.
• Develop and implement solutions to monitor data pipeline health, identify data anomalies, and proactively address data quality issues.
• Ensure the data platform adheres to global data privacy regulations (e.g., GDPR, CCPA) and TCCC's internal security protocols, especially for multi-tenant data access by bottlers and OEMs.
• Implement robust logging, monitoring, and alerting for data pipelines and data platform components.

• Collaborate closely with the Global Product Owner for Unified IoT, GEP Hardware/Software Engineering, Enterprise Digital Technology Solutions (IT), and Experience Design teams to ensure seamless data integration from connected devices.
• Work with equipment OEMs (e.g., Lancer, Cornelius, True, Imbera) to integrate their telemetry systems and ensure data capture adheres to TCCC's standards.
• Contribute to…