Lead Data Architect

Description

As of November 1, 2025, Sunoco LP has successfully completed its acquisition of Parkland Corporation. For more information, please visit  Competitive Benefits. Meaningful Extras. Unmatched Value.

As the Data Architecture Lead, you will guide the transformation and migration of our data ecosystem towards a modern, target-state architecture built on Azure and Databricks, while ensuring continuity and integration with existing legacy environments (primarily AWS-native data lake and SQL Server) as needed. This role demands a unique blend of technical expertise, strategic vision, and leadership to drive innovation and deliver business value through data.

• Platform Modernization & Migration:
  Driving the transition from legacy systems to Azure-based architecture, ensuring interoperability and minimal disruption.
• Architecture & Engineering:
  Designing and implementing a high-performing data platform leveraging Databricks, cloud-native services, and common data models.
• Integration & Enablement:
  Ensuring the platform provides seamless data access and sharing capabilities, enabling stakeholders to easily discover, consume, and utilize trusted data assets.
• AI & GenAI Enablement:
  Helping build platform capabilities to support advanced AI workloads and emerging technologies for data-driven decision‑making.
• Data Governance & MDM:
  Implementing strong governance frameworks and Master Data Management to maintain data integrity and compliance.
• Agile Delivery:
  Applying agile methodologies and tools such as Jira and Service Now to enable rapid iteration and continuous improvement.
• Strategic Planning:
  Developing and executing a comprehensive roadmap for data platform modernization, driving migration from legacy systems (AWS-native data lake, SQL Server) to Azure and Databricks; continuously monitoring technology trends, emerging tools, and business needs to refine strategy and foster innovation.
• Enterprise Data Architecture:
  • Data Strategy & Architecture:
    Defining architecture principles and standards to ensure consistency across systems and platforms; developing and maintaining a comprehensive enterprise data architecture that aligns with organizational goals and supports the modernization roadmap; creating and maintaining enterprise-wide data standards, guidelines, and best practices for modeling, integration, and governance; providing strategic leadership on emerging data technologies such as knowledge graphs, real‑time analytics, and generative AI data foundations.
  • Data Modeling & Master Data Management:
    Designing logical and canonical data models that ensure interoperability, scalability, and alignment with enterprise architecture principles; building and maintaining canonical data models to standardize data exchange across applications, integration layers, and business domains; leading enterprise master data management (MDM) strategy and implementation, including domain modeling, survivorship rules, golden record creation, and stewardship processes.
  • Data Governance, Quality & Compliance:
    Collaborating with stakeholders to develop and enforce data governance policies, procedures, and standards; defining and operationalizing data lifecycle management processes, including creation, storage, usage, archival, and deletion; designing end-to-end data and analytics solutions that meet business requirements and align with organizational goals; implementing data quality frameworks covering profiling, cleansing, monitoring, and remediation.
  • Data Platforms & Infrastructure:
    Leading data modernization initiatives, including migration planning, platform selection, and hybrid/multi‑cloud strategies; architecting and optimizing enterprise data platforms including data lakes, warehouses, and Lakehouse environments; implementing metadata management strategies such as business glossaries, lineage, and cataloging to enhance data discoverability and trust.
  • Data Integration & Interoperability:
    Developing enterprise data integration strategies using APIs, event‑driven architectures, ETL/ELT pipelines, and streaming platforms; collaborating with engineering teams to design APIs that enable efficient…