Director, Global Data Engineering

Circle K • Charlotte, NC

2d

About The Position

Circle K is seeking a transformational, people-focused, and execution-oriented Director, Global Data Engineering. Reporting to the Head of Global Data Engineering, Architecture & Enablement, this leader will own the enterprise Data Engineering function and lead globally distributed teams responsible for delivering trusted, scalable, secure, and reusable data products. This role combines organizational leadership, engineering excellence, modernization, delivery execution, and talent development. The Director will translate enterprise strategy into measurable outcomes while partnering across Data Architecture, Platform Engineering, Analytics Engineering, Governance, Data & Analytics teams, Security, and business teams.

Requirements

• Bachelor’s degree in Computer Science, Information Systems, Engineering, Mathematics, or a related field
• 12+ years of progressive experience in data engineering, data platforms, analytics engineering, or a related technology field.
• 5+ years leading managers and large, globally distributed engineering organizations.
• Demonstrated success building high-performing teams and delivering large-scale cloud data modernization or enterprise transformation programs.
• Strong experience with product-oriented delivery models, DataOps, DevOps, engineering governance, and reliable production support.
• Ability to connect business strategy, architecture, technology, talent, and execution, and communicate effectively with executives, engineers, and business partners.
• Strong knowledge of modern cloud data ecosystems, including Azure, Snowflake, Databricks, lakehouse and data warehouse architectures, ETL/ELT, APIs, batch and streaming integration, dimensional and semantic modeling, metadata, lineage, data quality, and secure data sharing.
• Understanding of the data-engineering capabilities that enable generative AI, agents, natural-language analytics, and machine learning while enabling observability, responsible AI controls, and protection of sensitive data.

Nice To Haves

• A master’s degree is preferred.

Responsibilities

• Set the vision, operating model, priorities, and standards for the global Data Engineering organization, leading through Senior Managers, Managers, and Engineering Leads.
• Build a high-performing, product-oriented engineering culture grounded in accountability, ownership, quality, innovation, and continuous improvement.
• Deliver reusable enterprise data products spanning source integration, batch and streaming ingestion, transformation, harmonization, data quality, dimensional modeling, analytical data marts, metadata, lineage, and documentation.
• Ensure engineering solutions support reporting, self-service analytics, machine learning, generative AI, agents, automation, and secure enterprise data sharing.
• Establish engineering practices for DataOps, DevOps, CI/CD, automated testing, infrastructure as code, observability, incident management, performance optimization, service levels, and operational support.
• Drive measurable improvements in delivery speed, predictability, quality, scalability, cost efficiency, and platform reliability.
• Partner with architecture, platform, analytics, governance, cybersecurity, product, and business leaders on solution design, technology decisions, investment priorities, and enterprise modernization.
• Recruit, coach, develop, and retain strong engineering talent; establish career paths, succession plans, and capabilities needed for future growth.
• Lead globally distributed teams through organizational and technology transformation while fostering inclusive, effective collaboration across a matrixed enterprise.
• Manage budgets, capacity, workforce plans, vendors, and strategic partners to align resources and investments with enterprise priorities and business value.
• Collaborate with Data Governance to embed ownership, certification, quality controls, metadata, lineage, privacy, and security into engineering practices so trusted data is understandable, discoverable, and usable.
• Simplify and modernize the enterprise data estate by retiring legacy patterns, improving interoperability across cloud platforms and consumption channels, and reducing unnecessary duplication and technical debt.
• Help integrate AI into both how data products are built and how the organization uses data, including applying AI-assisted development, testing, documentation, data quality, observability, and automation across the engineering lifecycle while maintaining appropriate engineering controls and human accountability.
• Ensure that generative AI, agents, natural-language analytics, machine learning, and intelligent applications are grounded in certified, secure, well-described, and context-rich data.
• Establish scalable patterns for AI-ready data products and evaluate emerging capabilities based on measurable improvements in productivity, quality, adoption, and business outcomes.

Benefits

• Circle K is an Equal Opportunity Employer.
• The Company complies with the Americans with Disabilities Act (the ADA) and all state and local disability laws.
• Applicants with disabilities may be entitled to a reasonable accommodation under the terms of the ADA and certain state or local laws as long as it does not impose an undue hardship on the Company.
• Please inform the Company’s Human Resources Representative if you need assistance completing any forms or to otherwise participate in the application process.
• Click below to review information about our company's use of the federal E-Verify program to check work eligibility: In English, In Spanish

What This Job Offers

• Job Type: Full-time
• Career Level: Director