Data Modeler/Architect

Accenture•Houston, TX

1d•$80,400 - $293,800•Hybrid

About The Position

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.

Requirements

6+ years of dedicated data modeling experience within enterprise environments, focusing heavily on conceptual and logical design in complex industrial, supply chain, or energy domains.
Proven track record of working directly with business stakeholders (such as analysts, data scientists, quants, and risk professionals) to gather requirements, as well as partnering effectively with Product Owners and Architects to execute technical roadmaps.
Mastery of data modeling methodologies (Dimensional Modeling/Kimball, 3NF/Relational) and proficiency with industry-standard modeling tools (e.g., ERwin, PowerDesigner, or modern visual/code-based modeling frameworks).
Strong conceptual understanding of physical supply chains, time-series data relationships, spatial/geographical hierarchies, and market fundamental data.
Familiarity with modern cloud data platform concepts and Medallion Architecture patterns (separating raw, conformed, and dimensional layers logically).

Nice To Haves

Familiarity with modern code-based data modeling and documentation frameworks (such as dbt-native modeling/tests).
Prior exposure to energy market fundamental data feeds (e.g., vessel tracking, EIA reports, production statistics).
Experience in Agile/Scrum delivery environments, working alongside Product Owners in feature grooming and backlog planning.
Experience with Unity Catalog, Databricks Workflows, Delta Live Tables / Lakeflow, Auto Loader, Change Data Feed, and materialized views.
Experience with cloud platforms such as Azure, AWS, or GCP.
Bachelor’s or Master’s degree in Computer Science, Data Management, Information Systems, Industrial Engineering, or a related quantitative field.

Responsibilities

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.
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.
Translate business concepts and domain rules into formal conceptual entity-relationship diagrams (ERDs) and logical data models (LDMs), establishing clear enterprise-wide data standards.
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.
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.
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.