Manager, Data Engineering

McDonald's Corporation•Chicago, IL

19h•Onsite

About The Position

McDonald’s Global Data & Analytics organization is seeking a Manager, Data Engineering to lead the design, delivery, and evolution of large-scale data products that support critical global business outcomes. This role is responsible for end-to-end technical ownership of data products, including roadmap execution, engineering excellence, and people leadership for a squad of data engineers. You will operate at the intersection of technology, product, and business, serving as the primary technical decision-maker for your data products while partnering closely with Product Managers, Architects, and key stakeholders across the enterprise. Success in this role requires deep technical fluency, strong leadership instincts, and a customer-focused mindset.

Requirements

Bachelor’s degree in Computer Science, Engineering, or a related field.
5+ years of hands-on experience in data engineering or related technical roles.
Proven experience leading or managing engineering teams in complex environments.
Strong working knowledge of cloud-based data platforms (AWS and/or GCP).
Experience building, deploying, and operating data pipelines at scale.
Experience working in Agile delivery models (sprint planning, stand-ups, retrospectives).
Strong communication and stakeholder management skills across a global, matrixed organization.
Detail-oriented, analytical, and able to independently reason through complex problems.

Nice To Haves

Experience with McDonald’s digital ecosystem, restaurant technology, or enterprise data platforms.
Familiarity with McDonald’s data systems and digital stack.
Experience using JIRA, Confluence, and ServiceNow or similar tools.
Experience working with monitoring, alerting, and incident management tooling.

Responsibilities

Own the technical vision, architecture, and evolution of assigned data products.
Develop and maintain a target-state technical roadmap, balancing functional enhancements, non-functional requirements (performance, reliability, scalability), and technical debt.
Serve as a deep subject-matter expert on your products, including: Data ingestion, transformation, and loading patterns, Table structures and semantic layers, Upstream and downstream integrations.
Evaluate whether existing solutions are fit for purpose and continuously evolve platforms using modern data engineering best practices.
Partner with Data and Solution Architects to deliver scalable, secure, and reliable data solutions.
Manage technical dependencies and interfaces across McDonald’s broader data ecosystem.
Establish engineering best practices for risk management, testing strategy, and production readiness.
Define and enforce non-functional requirements throughout the product lifecycle.
Manage temporary solutions and technical debt at the squad level.
Ensure high standards of data quality, reliability, observability, and performance from an end-user perspective.
Participate in and lead data quality initiatives across McDonald’s data platforms.
Oversee testing strategies and validate quality of outputs delivered by internal and external development teams.
Participate in release planning and deployment coordination in partnership with Product and Deployment teams.
Serve as a technical escalation point for complex incidents, defects, or architectural decisions.
Partner closely with Product Managers to own and execute product roadmaps aligned to business priorities.
Map product roadmaps into clear release plans and communicate progress to markets and stakeholders.
Act as an advocate for the global end-user experience, ensuring solutions scale across functions and geographies.
Conduct or support business acceptance for features and epics based on defined success criteria.
Actively gather end-user feedback and translate insights into roadmap and product improvements.
Manage accountability with third-party technology vendors involved in product delivery.
Communicate complex technical concepts clearly to stakeholders at varying levels of technical depth.
Serve as a catalyst for collaboration across Data & Analytics, Technology, and business teams.
Partner with Initiative Leads, Product Managers, Architects, and Program teams to maximize value delivery across multi-product initiatives.
Own and prioritize the product backlog, including participation in intake triage and decomposition of ideas into epics and features.
Ensure alignment and coordination across dependent data products and platforms.
Provide people leadership for a team of data engineers, including coaching, performance management, and career development.
Manage squad capacity across development, defect resolution, market enablement, and testing.
Forecast capacity needs and partner with Demand Management to engage third-party resources when required.
Ensure work flows through McDonald’s Demand Management and Agile delivery processes effectively.
Foster a culture of engineering excellence, accountability, and continuous improvement.