C

CHEP

Pallet pooling and supply chain optimization

Enterprise Data Architect

Data ManagementConfirmed live in the last 24 hours
Full-timeNo salary listed

About the Job

Requirements

  • At least 5 years in a data architecture-related role.
  • Experience designing and implementing data and information solutions, including continuously monitoring and improving those solutions.
  • Experience developing data management best practices and implementing data principles across an organization.
  • Experience addressing data and information architecture considerations across cloud platforms, integration, data management, analytics, and business intelligence.
  • Significant experience in enterprise data architecture within a complex global organization.
  • Experience defining enterprise data and information models.
  • Understanding of the DAMA Data Management Framework and the relationship between data architecture and wider data management capabilities.
  • Working knowledge of data management disciplines including data quality, master data, metadata, and data lineage.
  • Strong understanding of how data architecture influences the quality, consistency, and trustworthiness of enterprise data.
  • Ability to translate business data challenges into practical architectural designs, standards, and recommendations.
  • Experience managing and maintaining technology architecture models.
  • Proven experience planning, organizing, and developing information and data architectures and systems.
  • Experience developing and applying data architecture principles, standards, patterns, and reference models in alignment with enterprise policies.
  • Knowledge of technology environments, including information systems, data architecture, and enterprise applications.
  • Proven track record contributing to overall enterprise architecture development, ideally within a TOGAF framework.
  • Ability to identify risks associated with business processes, operations, information systems, and technology projects.
  • Ability to explain technical topics to audiences without a technical background.

Responsibilities

  • Define and develop data architecture models and their lower-level components.
  • Contribute to and enable delivery of the enterprise data strategy by developing target data architecture, information models, and architectural roadmaps.
  • Develop and maintain enterprise data architecture principles, standards, patterns, and reference models.
  • Support creation of trusted data through effective data architecture, focusing on how data is created, managed, and consumed across critical business processes.
  • Drive architectural understanding of master data, metadata, data lineage, and enterprise data flows to support business decision-making and operational effectiveness.
  • Act as lead data architect on critical programs, engaging stakeholders and partnering with the Architecture Community.
  • Lead and recommend development of global standard core business system and data processes, ensuring the overall design is robust, coherent, and meets the future operating model.
  • Drive development of the organization's data architecture in collaboration with the business.
  • Document the as-is data landscape, identify key risks, and recommend mitigations.
  • Develop and communicate data standards and data models to facilitate classification of all data elements.
  • Analyze technology industry and market trends, focusing on developments in data analytics, machine learning, artificial intelligence, mobile, and cloud agile technologies, and determine their potential enterprise impact.
  • Develop future-proof data architecture designs for complex enterprise software.
  • Establish priorities and strategies consistent with business goals and economic viability.
  • Research options and propose data architecture solutions for organizational technology needs, including new and emerging technologies.
  • Develop and maintain enterprise conceptual, logical, and physical data models.
  • Define architectural standards and patterns for managing master data, reference data, and shared business data assets.
  • Partner with business and technology teams to understand architectural drivers of recurring data quality issues and recommend sustainable design improvements.
  • Support identification of data risks and control weaknesses within source systems and data movement processes.
  • Work across technical teams to ensure consistent understanding of key data entities and their lifecycle across the enterprise.
  • Develop and communicate data architecture standards, information models, and classification structures aligned with enterprise data governance policies and standards.
  • Deliver architecture designs across multiple integrated technologies and platforms in accordance with stage gates, milestones, and business objectives.
  • Resolve complex architectural issues spanning business processes, applications, integration platforms, and data domains.
  • Balance enterprise standardization with legitimate regional, functional, and program requirements.
  • Identify root causes of data inconsistency, duplication, and quality issues across complex system landscapes.
  • Assess architectural trade-offs involving data quality, interoperability, cost, risk, and delivery timescales.
  • Influence cross-functional decisions where ownership is distributed across business and technology teams.
  • Document and maintain critical enterprise data flows to support transparency, impact assessment, and change management.
  • Document and govern key business data entities, master data domains, and associated metadata through agreed data architecture standards.
  • Use data architecture to improve visibility of data quality risks, controls, and dependencies across critical source systems.
  • Document and maintain reference data information architectures.
  • Ensure projects and programs align with agreed data architecture principles and standards.
  • Apply and adhere to data and information system principles through technical change.

Desired Qualifications

  • TOGAF Foundation or Practitioner qualification.
  • DAMA CDMP qualification.
  • DCAM qualification.
  • SAP data architecture experience.
  • Bachelor's degree in Information Systems, Computer Science, Engineering, or a related discipline.

About the Company

CHEP

Pallet pooling and supply chain optimization

CHEP provides pallet pooling and supply chain solutions. It rents out reusable pallets and containers to clients in consumer goods, retail, and manufacturing, using a subscription-based model and a networked pooling system to move goods efficiently. The service works by supplying standardized, reusable pallets that are circulated among customers, tracked, cleaned, and reused, with optional supply chain consulting and logistics optimization to increase efficiency. Compared with competitors, CHEP operates at a global scale with an integrated, end-to-end pallet pooling network and value-added services, focusing on reducing costs and waste across the supply chain. Its goal is to help customers streamline logistics, lower total costs, and improve sustainability by maximizing reuse of packaging and minimizing waste.

Company size
5,001-10,000
Company stage
Grant
Total funding
$30K
Headquarters
Orlando, FL
Founded
2001

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