Internship Global Data Analyst Jobs (NOW HIRING)

Circle K is a global leader in convenience retail and fuel, operating in 24 countries and serving millions of customers every day. We are advancing our digital and data transformation through modern cloud platforms, trusted data products, artificial intelligence, and analytics that enable faster decisions and create value across the enterprise.

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.

• 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.

The Director will help integrate AI into both how data products are built and how the organization uses data. This includes applying AI-assisted development, testing, documentation, data quality, observability, and automation across the engineering lifecycle while maintaining appropriate engineering controls and human accountability.

This leader will also ensure that generative AI, agents, natural-language analytics, machine learning, and intelligent applications are grounded in certified, secure, well-described, and context-rich data. Working with key partners, the Director will establish scalable patterns for AI-ready data products and evaluate emerging capabilities based on measurable improvements in productivity, quality, adoption, and business outcomes.

• Bachelor's degree in Computer Science, Information Systems, Engineering, Mathematics, or a related field; a master's degree is preferred.
• 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.

You bring 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. You also understand 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. You do not need to be the hands-on expert in every platform or AI technology, but you must be able to guide technical direction, distinguish durable architecture from experimentation, ask the right questions, and hold teams accountable for sound, secure, and scalable engineering decisions.

You are a strategic thinker and pragmatic operator who can lead change at enterprise scale. You develop strong leaders, influence across organizational boundaries, simplify complexity, and create clarity around priorities and accountability. You balance innovation with operational discipline and consistently connect engineering investments to customer and business outcomes.

This is an opportunity to shape how Circle K builds, governs, and uses data worldwide. The Director will strengthen the engineering organization, accelerate delivery of trusted data products, and create the scalable foundation needed for data, analytics and AI to deliver meaningful business value.

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