Data Modeler/Architect

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The beginning of a new Data & AI decade that will reshape work and society has begun. Accenture is stepping boldly into this future with a clear strategy and purpose: to help clients optimize and reinvent their business with data & AI - backed by a $3B investment and commitment to our people to do industry-defining work.

With over 45,000 professionals dedicated to Data & AI, Accenture's Data & AI organization brings together our Experienced Innovation, Strategic Investment, Exceptional Talent, and Power Ecosystem.

You are

A strong Data Modeler / Data Architect Lead who can provide technical leadership, architectural direction, and engineering governance for enterprise data platform initiatives. This role is not intended for a hands-on-only developer profile. The ideal candidate should be able to guide the team on overall architecture, data engineering best practices, design patterns, governance, data quality, and scalable implementation approaches. The candidate should be an independent thinker who can evaluate requirements, challenge weak designs, influence stakeholders, and ensure that sound data engineering principles are consistently adopted across the team.

Position Summary

We are seeking a Senior Data Modeler to spearhead the conceptual and logical data design for our Commercial Energy Market Fundamentals and Supply Chain analytics platform. In this role, you will act as the crucial bridge between business vision and technical execution.

You will work hand-in-hand with key stakeholders-including Data Scientists, Risk Managers, and Market Analytics teams-to uncover analytical needs, conduct data-scoping workshops, and translate complex physical energy concepts into rigorous data models. Once designed, you will engage closely with Product Owners and Data Architect to guide backlog prioritization, define structural requirements, and oversee successful implementation across a Medallion Architecture.

Key Responsibilities

• Stakeholder Collaboration & Requirements Discovery: Partner directly with Market Analytics teams, Data Scientists, and Risk Managers to understand analytical workflows, define key metrics, and capture conceptual data requirements for energy supply/demand, logistics, and curves.
• Domain Taxonomy & Semantic Modeling: Architect enterprise-grade taxonomies, conformed dimensions, and hierarchical structures for core energy domains: Market Balances: Global import/export flows, production, consumption, and reserve metrics.Logistics & Spatial Data: Vessel tracking movements, port hierarchies, routing nodes, and freight structures.Asset Frameworks: Refinery and plant networks, operational status tracking, and capacity hierarchies.Market Curves & Pricing: Time-series pricing structures, historical curves, and market assessment taxonomies.
• Conceptual & Logical Design: Translate business concepts and domain rules into formal conceptual entity-relationship diagrams (ERDs) and logical data models (LDMs), establishing clear enterprise-wide data standards.
• Architectural & Product Handoff: Engage proactively with P66 Product Owners to help shape the data product roadmap, and collaborate with Data Architect to ensure logical models align with enterprise target-state architecture and implementation standards.
• Medallion Architecture Alignment: Define the structural contracts and semantic transformations as data moves from ingestion into structured, conformed Silver layer entities and business-optimized Gold layer analytical models.
• Governance & Model Standardization: Establish enterprise data modeling standards, naming conventions, and best practices. Partner with data governance teams to maintain the enterprise data dictionary and end-to-end logical lineage.

Travel may be required for this role. The amount of travel will vary from 0 to 100% depending on business need and client requirements.