Manager, Data Engineering

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.