Senior Manager, Data Engineering

Full-time - Senior

Chicago, IL

About the position

McDonald’s Global Technology – Data & Analytics team is looking to hire an Enterprise Data Analytics & AI (EDAA) Senior Manager, Data Engineering who can lead the solution, design and development of a new universal semantic layer tool for McDonald’s. As a Senior Manager, Data Engineering you will be responsible for designing the solution, managing the engineering squad to build the solution, and partnering with the business product owner to deploy and drive adoption in the markets and business functions. The semantic layer tool will help drive the standardization of key metrics and KPIs, drive better access to data, and enable easier data blending across our lake. Consumers of the semantic layer include business users, tech teams and other applications. To achieve this, you will work closely with the business product team and collaborate with other cross functional teams like enterprise and solution architecture, data governance, insights, and more. Your expertise in data engineering, analytics, AI, and BI architecture will play a crucial role in delivering a high-quality data semantic layer product and enabling one McDonald’s way of data-driven decision-making.

Responsibilities

• Leads the design and architecture of the semantic layer solution to enable scalable, efficient data access for business users, applications, insights users, and tech teams
• Works with cross functional teams like solution architecture, enterprise architecture, data governance, cybersecurity, and functional stakeholders to ensure the semantic layer solution meets all priority functional and nonfunctional requirements
• Works with business product owner, data governance, product and insights teams to leverage the semantic layer to drive standardization of KPIs and metrics to establish One McDonald’s way of measurement
• Manages a data engineering squad to develop the MVP solution and future enhancements and iterations
• Drives key design decisions for the full stack semantic layer solution throughout design and build, coordinating between different stakeholders and leaders for input
• Collaborates with business product owner, in two in the box model, to prioritize work and manage product roadmap
• In collaboration with business product owner, engages with market stakeholders to identify how the semantic layer solution can help solve their business problems
• Establishes and maintains a solid understanding of the technical details of all data domains and clearly understands what business problems are being solved and capabilities enabled with their data
• Works with product and platform teams to integrate with the semantic layer, determining the right patterns to leverage
• Advocates for self-service analytics by enabling non-technical users to easily access and analyze data
• Collaborates with AI team to ensure the semantic layer enables key AI use cases (I.e., Agentic AI, NLQ queries, ML-driven insights)
• Manages integrations with other products and tools, establishing data contracts and core PDR principles
• Works with data products and architecture teams to maintain standardized data models to provide a consistent view across domains and products
• Leads solutioning of real-time and batch processing strategies to balance freshness, cost, and speed in data delivery
• Ensures the data engineering team has the right skillsets and capacity to deliver on the target state solution
• Stays up to date on industry trends and emerging technologies to enhance the semantic layer’s capabilities

Requirements

• Bachelor's or Master's degree in Computer Science or related engineering field and deep experience with AWS or GCP infrastructure
• Experience leading a data engineering squad
• Experience building a data product, through solution, design, build, deploy and scale phases
• Strong SQL knowledge and experience with data modeling, dimensional modeling, and cloud data warehouse concepts
• 5+ years of proficiency in programming languages commonly used in data engineering, such as Python and SQL
• 5+ years of hands-on experience with data modeling, ETL development, and data integration techniques
• Working knowledge of relational and dimensional data design and modeling in a large multi-platform data environment
• Expert knowledge of quality functions like cleansing, standardization, parsing, de-duplication, mapping, hierarchy management, etc.
• Expert Knowledge of data, master data and metadata related standards, processes and technology
• Ability to drive continuous data management quality (i.e. timeliness, completeness, accuracy) through defined and governed principles
• Ability to perform extensive data analysis (comparing multiple datasets) using a variety of tools
• Demonstrated experience in data management & data governance capabilities
• Excellent problem solver - use of data and technology to solve problems or answer complex data related questions
• Excellent communication and collaboration skills to work effectively in cross-functional teams

Nice-to-haves

• Experience with JIRA and Confluence as part of project workflow and documentation tools is a plus
• Experience with Agile project management methods and terminology a plus
• Experience with semantic layer SaaS tools (i.e. Cube, AtScale, Looker)
• Experience with GraphQL

Benefits

• Health and welfare benefits
• 401(k) plan
• Adoption assistance program
• Educational assistance program
• Flexible ways of working
• Time off policies (including sick leave, parental leave, and vacation/PTO)
• Bonus eligible based on individual and company performance
• Long term incentive eligible for stock or other equity grants