Sr Director, Data Engineering - Consumer Data & Analytics

McDonald's Corporation • Chicago, IL

8d • $237,102 - $296,377

About The Position

The Data & Analytics team enables data-driven decision making across the enterprise by delivering scalable data platforms, advanced analytics capabilities, AI/ML foundations, and trusted data products. We empower business and technology teams with modern data infrastructure, governance, and engineering practices to transform data into actionable insights and business value.

We are seeking a Senior Director, Consumer Data Engineering, to lead the vision, strategy, and execution of data engineering capabilities across the Consumer domain. This leader will be responsible for building and scaling a high-performing engineering organization that develops reliable, secure, and scalable data platforms and products powering customer analytics, artificial intelligence, personalized consumer experiences, and data-driven decision-making across global markets.

The Senior Director will oversee teams responsible for Customer Data (including Customer 360, customer profiles, identity resolution, consent, and governance), Marketing Activation (including customer data platforms CDP, campaign activation pipelines, and audience syndication), and Clickstream Analytics across digital touchpoints. This leader will establish the strategic direction for consumer data engineering, drive modernization and strategic insourcing initiatives, industrialize robust data pipelines, and establish certified semantic data layers that empower business self-service while enforcing stringent customer data privacy and regulatory compliance standards.

This role partners closely with Marketing, Digital Customer Experience, Data Science, Platform Engineering, Cybersecurity, and global market business leaders to ensure the organization can effectively leverage customer data as a strategic asset. This role combines deep technical expertise, organizational leadership, operational excellence, and executive-level stakeholder management to enable consumer data transformation at enterprise scale.

Requirements

• Bachelor's degree in Computer Science, Engineering, Information Systems, or a related technical field. Advanced degree preferred.
• 15+ years of progressive experience in data engineering, software engineering, data platform development, or related technology disciplines.
• 8+ years of experience leading large-scale engineering organizations, including direct leadership of managers and senior technical leaders.
• Demonstrated success developing and executing enterprise data strategies that support customer analytics, marketing activation, personalization, artificial intelligence, and business transformation initiatives.
• Deep expertise in modern data platforms, data architecture, customer data integration (e.g., CDP, Customer 360), data warehousing, data lakes, and large-scale distributed data processing technologies.
• Strong understanding of data product lifecycle management, engineering best practices, and platform operating models.
• Proven experience building and scaling highly available, secure, and resilient data platforms supporting enterprise consumer workloads.
• Extensive experience with data modeling, ETL/ELT design, data integration, and information management practices.
• Strong knowledge of data governance, customer identity resolution, master data management, metadata management, data quality frameworks, and regulatory compliance requirements (e.g., GDPR, CCPA, consumer privacy).
• Experience establishing engineering standards, architectural principles, operational excellence practices, and performance metrics across large organizations.
• Strong understanding of cloud-based data ecosystems (e.g., Google Cloud Platform, AWS) and modern platform architectures.
• Experience managing significant technology budgets, vendor relationships, and strategic technology investments.
• Track record of successfully leading large-scale transformation programs, organizational change initiatives, or talent insourcing transitions.
• Exceptional executive communication, stakeholder management, and influencing skills.
• Demonstrated ability to build partnerships across business and technology organizations.
• Strong analytical, strategic thinking, and problem-solving capabilities.

Nice To Haves

• Experience supporting consumer-facing analytics, customer journey analytics, MarTech integrations (e.g., Braze, mParticle), and customer segmentation/personalization engines.
• Experience leading global teams across multiple regions and time zones.
• Familiarity with Agile delivery methodologies, PI planning, and modern product operating models.
• Experience establishing data observability, monitoring, reliability, and operational excellence programs.
• Experience with strategic talent insourcing and transitioning contractor-heavy teams to sustainable internal engineering models.
• Experience working within large, complex, matrixed global organizations or high-volume digital consumer enterprises.
• Relevant industry certifications in data, cloud, architecture, or technology leadership disciplines.

Responsibilities

• Define and execute the data engineering strategy, roadmap, standards, and operating model for the Consumer data domain in alignment with enterprise objectives.
• Establish long-term vision for consumer data platforms, customer data products (e.g., Customer 360, CDP, clickstream analytics), data architecture, and engineering capabilities to support evolving marketing, digital, and personalization needs.
• Serve as an executive advisor and thought leader on consumer data engineering strategy, customer identity architecture, data privacy, governance, and platform investments.
• Lead and develop a large, geographically distributed team of data engineering leaders, managers, architects, and engineers while fostering a culture of innovation, accountability, inclusion, and continuous improvement.
• Drive strategic talent and insourcing initiatives, building sustainable internal engineering capability and transitioning vendor/contractor capacity into high-performing internal engineering squads.
• Ensure effective communication and collaboration across globally distributed teams and stakeholders.
• Drive the design, implementation, and optimization of scalable data ecosystems that support customer analytics, machine learning, marketing activation, and self-service business intelligence.
• Partner with Enterprise Architecture and Data Platform Engineering to define target-state consumer data architecture and ensure scalable solutions align with enterprise technology and cloud standards.
• Drive modernization initiatives and technology transformations that improve customer data accessibility, identity resolution, real-time event streaming, interoperability, automation, and operational excellence.
• Oversee the development, industrialization, and lifecycle management of enterprise consumer data products (including Customer 360, marketing activation feeds, and clickstream analytics), ensuring reliability, scalability, observability, security, and performance.
• Deliver robust data pipelines and certified semantic gold data layers that empower business units and markets to self-service reporting and analytics, avoiding centralized reporting bottlenecks.
• Develop key performance indicators and operational metrics to measure platform health, pipeline freshness, service performance, quality, adoption, and business impact.
• Champion customer data privacy, consent management (e.g., GDPR/CCPA compliance), data quality, metadata management, and master data management across all consumer touchpoints.
• Ensure consumer data platforms and engineering processes are designed with resiliency, zero-trust security, privacy-by-design, and regulatory compliance requirements at the forefront.
• Establish clear architectural boundaries and interface contracts between core engineering pipelines and data science / algorithmic modeling teams.
• Partner with senior business and technology leaders across MarTech, Digital Customer Experience, Loyalty, and global markets to identify opportunities to leverage customer data and accelerate business value.
• Build strong collaboration across data science, analytics, product management, cybersecurity, infrastructure, and software engineering teams.

Benefits

• sabbatical program
• tuition assistance
• flexible work arrangements
• comprehensive health insurance, which includes medical, prescription drug, mental health, dental and vision coverage
• life insurance

What This Job Offers

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