Enterprise Data Architect

Welcome to Love's: The Enterprise Data Architect is responsible for defining, governing, and advancing the organization's enterprise data architecture across cloud and hybrid environments. This role establishes scalable, secure, and cost-efficient data foundations that enable enterprise analytics, AI-driven insights, and data-informed decision-making.

This role owns end-to-end data architecture, including ingestion, integration, modeling, transformation, and consumption across platforms such as Snowflake, dbt, HVR/Fivetran, SQL Server, SAP HANA, Power BI, and Sigma. The Enterprise Data Architect serves as the primary integration point across enterprise platforms, including SAP and Palantir.

Job Functions:

Architecture & Strategy

• Define and maintain enterprise data architecture and long-term roadmap aligned to business and operational priorities
• Design scalable, secure, and high-performing data platforms across cloud and hybrid environments
• Establish architectural standards, governance frameworks, and design patterns across the data lifecycle
• Evaluate emerging technologies and drive continuous platform innovation

Data Platform & Engineering

• Architect and optimize batch and real-time data ingestion and replication processes
• Design and oversee transformation frameworks (e.g., dbt) to enable modular, testable, and reusable data models
• Integrate data across SAP HANA, SAP Data Sphere, SQL Server, and SaaS platforms into governed environments
• Lead modernization efforts from legacy systems to cloud-native architectures
• Implement CI/CD and DevOps best practices for data pipelines and analytics workflows

Data Modeling & Performance

• Develop and govern conceptual, logical, and physical data models
• Apply dimensional and data vault modeling techniques to support enterprise analytics
• Optimize platform performance, scalability, and cost efficiency, particularly within Snowflake environments

Analytics Enablement

• Partner with BI teams to design semantic layers and curated datasets
• Enable scalable analytics through tools such as Power BI and Sigma
• Promote self-service analytics through strong data design, governance, and documentation standards
• Optimize semantic models, aggregations, and query performance

Governance, Security & Quality

• Establish and enforce data governance frameworks, including data quality, lineage, and metadata management
• Implement secure, role-based access controls across platforms
• Ensure compliance with internal policies and regulatory requirements

Leadership & Collaboration

• Translate business and technical requirements into scalable data solutions
• Lead architecture reviews and guide enterprise data initiatives
• Mentor data engineers and analytics practitioners
• Contribute to and support a Data & Analytics Center of Excellence (CoE)

AI & Innovation

• Leverage AI and automation to improve data quality, pipeline efficiency, and analytics delivery
• Identify and implement AI-driven capabilities across the data lifecycle
• Promote a culture of innovation, experimentation, and continuous improvement

• Bachelor's degree in Computer Science, Information Systems, Engineering, or related field (Master's preferred)
• 8+ years of experience in data architecture and/or data engineering
• Experience designing, implementing, and scaling enterprise-grade data platforms
• Experience with data governance, metadata management, and data quality frameworks
• Experience implementing CI/CD and DevOps practices for data workflows
• Snowflake or cloud platform certifications
• Experience in large, complex, or multi-entity organizations
• Experience establishing or contributing to a Data & Analytics CoE

Skills and Physical Demands:

• Advanced SQL and data modeling (dimensional, normalized, data vault)
• Expertise in cloud data platforms (e.g., Snowflake or similar)
• Data integration tools (e.g., HVR, Fivetran, or equivalent)
• Data transformation frameworks (dbt preferred)
• Business intelligence tools (Power BI, Sigma, or similar)
• Data architecture across hybrid cloud and on-prem environments
• API-based integrations and/or streaming data architectures
• ERP data integration experience (e.g., SAP HANA, SAP Data Sphere)
• Data governance, lineage, and metadata management tools
• CI/CD pipelines and DevOps practices for data engineering
• Strong stakeholder engagement and partnership skills
• Ability to communicate complex technical concepts to non-technical audiences
• Collaboration across cross-functional and technical teams
• Adaptability in a fast-paced, evolving technology environment
• Mentorship and team development capabilities

Fueling customers' journeys since 1964, innovation leads the way for this family-owned and operated business headquartered in Oklahoma City. With nearly 40,000 team members, travel stops are the core business along with products and services that provide value for professional drivers, fleets, traveling public, RVers, alternative energy and wholesale fuel customers. Giving back to communities and an inclusive workplace are hallmarks of the award-winning culture.