Director, Data Architect – Global Equipment Platforms

Jobtailor; Atlanta (GA); On-site; USD 140,000 - 190,000; Full time

Job summary

GEP is seeking an expert to define and champion the Enterprise Data Architecture across telemetry, operational events, product analytics, and AI use cases. You will establish canonical data models and data contracts, guiding data flows from source systems to downstream applications.

You will partner with engineering and platform teams to ensure architecture standards are scalable, secure, and governance-driven, enabling AI-ready capabilities across the organization.

Qualifications

• 10+ years in data architecture, enterprise data platforms, data engineering, analytics architecture, or related technical leadership roles.
• Experience defining data architecture across complex, multi-system enterprise environments.
• Strong experience with cloud data platforms, lakehouse or warehouse architectures, data modeling, metadata, semantic layers, APIs, and data integration patterns.
• 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.
• Strong understanding of data governance, quality, lineage, access control, classification, and stewardship.
• Ability to translate complex business needs into clear architectural guidelines.

Responsibilities

• Define GEP’s Enterprise Data Architecture and modernization roadmap.
• Evaluate existing data architecture, platforms, and capabilities across GEP; identify gaps and define target-state architecture.
• Lead the definition of enterprise data architecture across telemetry, events, analytics, AI use cases.
• Establish canonical data models for core entities and data products.
• Define patterns for data flows across source systems, APIs, and downstream apps.
• Partner with engineering and architecture teams to ensure standards are implementable, scalable, and secure.
• Define and govern data contracts between source systems, OEMs, vendors, and data consumers.
• Establish and evolve business ontologies and knowledge models for consistent data interpretation and AI readiness.

Skills

Data Architecture

Data Engineering

Analytics Architecture

Data Modeling

Metadata Management

APIs

Data Integration

Canonical Data Models

Enterprise Semantic Layers

Data Contracts

Tools

Microsoft Fabric

Data Hub

Unified IoT

KOS

FOS

Job description

• Define GEP’s Enterprise Data Architecture


• Evaluate existing data architecture, platforms, and capabilities across GEP and the broader enterprise ecosystem; identify gaps and opportunities; and define a target-state architecture and modernization roadmap aligned to enterprise standards, business priorities, and future-state digital and AI capabilities.


• Lead the definition of GEP’s enterprise data architecture across equipment telemetry, operational events, service data, product analytics, customer-facing insights, and AI/ML use cases.


• Establish canonical data models for core entities such as equipment, devices, outlets, customers, bottlers, telemetry events, service events, products, consumption, configurations, and operational states.


• Define architecture patterns for how data flows across source systems, Unified IoT, KOS, FOS, Microsoft Fabric, Data Hub, APIs, data products, and downstream applications.


• Partner with GEP Engineering, Platform, Unified IoT, and broader global architecture and technology teams to ensure data architecture standards are implementable, scalable, secure, and operationally sustainable.


• Define and govern data contracts between source systems, OEMs, vendors, platform teams, and data consumers.


• Establish and evolve business ontologies and knowledge models that define the relationships between equipment, telemetry, products, customers, service events, and operational processes, enabling consistent data interpretation, interoperability, discoverability, and AI-ready capabilities.

Requirements

• 10+ years in data architecture, enterprise data platforms, data engineering, analytics architecture, or related technical leadership roles.


• Experience defining data architecture across complex, multi-system enterprise environments.


• Strong experience with cloud data platforms, lakehouse or warehouse architectures, data modeling, metadata, semantic layers, APIs, and data integration patterns.


• 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.


• Strong understanding of data governance, quality, lineage, access control, classification, and stewardship.


• Ability to translate complex business needs into clear architectural guidelines.

Core Competencies

Demonstrates extensive expertise in defining and governing enterprise data architecture, including cloud data platforms, data modeling, and data integration patterns. Capable of translating complex business requirements into actionable architectural guidelines while ensuring data governance and quality.

Highest-signal resume keywords

• Data Architecture


• Cloud Data Platforms


• Data Modeling


• Data Governance


• Data Integration Patterns

ATS Optimization Keywords

Hard Skills

• Data Architecture


• Data Engineering


• Analytics Architecture


• Data Modeling


• Metadata Management


• APIs


• Data Integration


• Canonical Data Models


• Enterprise Semantic Layers


• Data Contracts

Soft Skills

• Leadership


• Collaboration


• Communication

Industry Keywords

• Enterprise Data Architecture


• Operational Events


• Telemetry Events


• AI/ML Use Cases


• Business Ontologies


• Knowledge Models

Tools & Technologies

• Microsoft Fabric


• Data Hub


• Unified IoT


• KOS


• FOS