Manager, Data Engineering

Department Overview

Duties

1. Data Product Ownership & Technical Strategy 

• 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. 

2. Engineering Excellence & Data Quality 

• 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. 

3. Stakeholder Partnership & Customer Obsession 

• 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. 

4. Collaboration & Cross-Team Delivery 

• 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. 

5. People Leadership, Capacity & Resource Management 

• 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. 

Qualifications

Required 

• 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. 

Preferred 

• 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. 

Additional Information 

• Minimal travel required. 


• Chicago-based role, working primarily on-site at McDonald’s Global Headquarters. 

Compensation

Bonus Eligible: EDIT

Long - Term Incentive: EDIT

Benefits Eligible: EDIT

Salary Range

The expected salary range for this role is $138,207.00 - $172,758.00 per year

 

The above represents the expected salary range for this job requisition. Ultimately, in determining your pay, we may also consider your experience, and other job-related factors.