This role pays less than
90%
of similar roles. Most pay
$191,175–$262,950
— the shaded band above.
At the midpoint, this role pays about
$161k
versus about
$227k
for comparable roles.
Based on 240 similar postings.
Employer
About The Coca‑Cola Company
The Coca-Cola Company is the world''s largest beverage company, producing and distributing iconic soft drinks, juices, water, and other beverages across more than 200 countries. Industry: Beverages & Consumer Goods
The Coca‑Cola Company currently has
3 open roles
on FindRole.
Director, Data Architect Global Equipment Platforms (Coca-Cola GEP) serves as a senior individual contributor leadership role within the Global Equipment Platforms team. This position is responsible for defining and governing the enterprise data architecture to support connected equipment capabilities like telemetry, predictive maintenance, and beverage quality intelligence. The successful candidate will establish canonical data models, define data contracts, and develop architectural patterns for data flow across systems including Microsoft Fabric, Data Hub, and various APIs. Key responsibilities include building scalable data products, ensuring semantic consistency, and establishing governance standards for metadata, lineage, and access control. The role requires expertise in cloud data platforms, lakehouse architectures, and IoT telemetry to solve complex problems regarding equipment connectivity and operational visibility. Essential skills include data modeling, knowledge models, and experience with tools like Databricks or Snowflake to enable AI-ready capabilities across the global ecosystem.
Define and govern the enterprise data architecture for the Global Equipment Platforms ecosystem.
Establish canonical data models and business ontologies for equipment, telemetry, and customer data.
Define data contracts to ensure semantic consistency across source systems, vendors, and internal consumers.
Create architectural standards for reusable data products including curated datasets, APIs, and feature layers.
Develop infrastructure that supports AI/ML use cases like predictive maintenance and beverage quality intelligence.
Establish data governance models for ownership, stewardship, and role-based access control.
Provide technical leadership to vendors and partners to ensure they follow defined architecture standards.
What we're looking for
Must have at least 10 years of experience in data architecture, enterprise data platforms, data engineering, or related technical leadership roles.
Experience defining data architecture across complex, multi-system enterprise environments is required.
Required expertise includes cloud data platforms, lakehouse/warehouse architectures, data modeling, metadata, semantic layers, APIs, and integration patterns.
Must have experience designing or governing data products, data contracts, canonical data models, or enterprise semantic layers.
Experience working across data engineering, product, software engineering, analytics, and business stakeholders is required.
Strong understanding of data governance, quality, lineage, access control, classification, and stewardship is required.
Experience with IoT, telemetry, connected devices, manufacturing, or industrial systems (preferred).
Experience with Microsoft Fabric, Azure, Databricks, Snowflake, or designing architectures for AI/ML and predictive analytics (preferred).
Data Architecture
Data Modeling
SQL
Python
Databricks
Microsoft Fabric
Azure Data Services
Data Governance
Master Data Management
Metadata Management
Data Warehousing
Machine Learning
Generative AI
Data Science
Cloud Data Platforms
Data Quality
Data Architecture
Data Governance
Master Data Management (MDM)
Snowflake
Databricks
AWS
Azure
GenAI
LLM
Data Engineering
API
Data Catalog
GxP
TOGAF
DAMA CDMP
PMP
TBM Frameworks
Information Architecture
Data Governance
Data Mesh
Metadata Management
Data Quality
ERwin
ER/Studio
ArchiMate
UML
AWS
GCP
Snowflake
Databricks
Iceberg
Collibra
Alation
Great Expectations