at McDonald's in Chicago, Illinois, United States
Job Description
Company Description:
McDonald’s evolving Accelerating the Arches growth strategy puts our customers and people first and demonstrates our competitive advantages to strengthen our brand. We are recognized on lists like Fortune’s Most Admired Companies and Fast Company’s Most Innovative Companies.
Doubling Down on the 4Ds (Delivery, Digital, Drive Thru, and Development)
Our growth pillars emphasize the critical role technology plays as the best-in-class, global omni-channel restaurant brand. Technology enables the organization through digital technologies, and improving the customer, crew and employee experience each and every day!
Global Technology forging the way
Leading the digitization of our business is the Technology organization made up of innovation specialists who build industry defining tech using the latest innovations and platforms, like AI and edge computing to deliver on the next set of groundbreaking opportunities for the business. We take on technology innovation challenges at an incredible scale, and work across global teams who are always hungry for a challenge! This provides access to compelling career paths for technologists. It’s bonus points when you get to see your family and friends use the tech you build at their favorite McD restaurant.
Job Description:
McDonald’s Global Technology – Supply Chain Data & Analytics team is looking to hire a Data Engineer who has a deep understanding of Data Product Lifecycle, Standards and Practices. You will be responsible for building scalable and efficient data solutions to support the company’s data products and analytics initiatives. As a Data Engineer, you will collaborate with data scientists, analysts, and other cross-functional teams to ensure the availability, reliability, and performance of data systems. You will take ownership of engineering modules, development and act as an experienced leader of other engineers. Your expertise in cloud computing platforms, technologies and data engineering best practices will play a crucial role in delivering high-quality data products and enabling data-driven decision-making.
Responsibilities:
+ Builds and maintains relevant and reliable data products that support the business needs. Develops and implements new technology solutions as needed to ensure ongoing improvement with data reliability and observability in-view.
+ Owns engineering modules and functionalities and supports them through a full development cycle
+ Leads a back-end engineering team and facilitates cross-functional relationships to solve relevant business issues
+ Hands on mentality and skills
+ Able to code, develop and test solutions
+ React JS and Node JS knowledge a must have – able to right code
+ Understanding and development of RESTful and other API protocols is crucial and a must have
+ Proficiency in data formats like JSON and XML
+ Knowledge of authentication methods (e.g., OAuth) and API documentation tools is vital
+ Clear understanding and capability to define, design and present Architecture models, data flow diagram and overviews using professional tools.
+ Participates in new software development engineering. Helps to define business rules that determines the quality of data, assists the product owner in writing test scripts that validates business rules, and performs detailed and rigorous testing to ensure data quality
+ Develops a solid understanding of the technical details of data domains, and clearly understands what business problems are being solved
+ Designing and developing data pipelines and ETL processes to extract, transform, and load data from various sources into AWS data storage solutions (e.g., S3, Redshift, Glue).
+ Implementing and maintaining scalable data architectures that support efficient data storage, retrieval, and processing.
+ Collaborating with data scientists and analysts to understand data requirements and ensure data accuracy, integrity, and availability.
+ Building and optimizing data integration workflows to connect data from different systems and platforms.
+ Monitoring and troubleshooting data pipelines, identifying and resolving performance issues and bottlenecks.
+ Ensuring data security and compliance with data governance policies and regulations.
+ Managing data infrastructure on AWS, including capacity planning, cost optimization, and resource allocation.
+ Staying up to date with emerging data engineering technologies, trends, and best practices, and evaluating their applicability to improve data systems and processes.
+ Documenting data engineering processes, workflows, and solutions for knowledge sharing and future reference.
+ Ability and flexibility to coordinate and work with teams distributed across time zones, as needed. For instance, early morning/late evening hours to coordinate with teams in India
Qualifications:
+ Bachelor’s or Master’s degree in Computer Science or related engineering field and deep experience with AWS infrastructure
+ 10+ years of strong experience in data engineering, preferably with AWS backend tech stack, including but not limited to S3, Redshift, Glue, Lambda, EMR, and Athena.
+ 7+ years of proficiency in programming languages commonly used in data engineering, such as Python.
+ 5+ years of hands-on experience with big data processing frameworks, such as Apache Spark.
+ 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
+ Solid understanding of SQL and database concepts.
+ 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
+ Restful API knowledge
+ React JS and Node JS
+ Experience in leading engineering teams in development efforts
+ Ability to perform extensive data analysis (comparing multiple datasets) using a variety of tools
+ Demonstrated experience in data management & data governance capabilities
+ Familiarity with data warehousing principles and best practices.
+ 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.
+ Experience with JIRA and Confluence as part of project workflow and documentation tools
Preferred Requirements:
+ Experience with Agile project management methods and terminology a plus
+ Experience with Prometheus, Grafana
Additional Information:
McDonald’s is an equal opportunity employer committed to the diversity of our workforce. We promote an inclusive work environment that creates feel-good moments for everyone. McDonald’s provides reasonable accommodations to qualified individuals with disabilities as part of the application or hiring process or to perform the essential functions of their job. If you need assistance accessing or reading this job posting or otherwise feel you need an accommodation during the application or hiring process, please contact mcdhrbenefits@us.mcd.com. Reasonable accommodations will be determined on a case-by-case basis.
McDonald’s provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to sex, sex stereotyping, pregnancy (including pregnancy, childbirth, and medical conditions related to pregnancy, childbirth, or breastfeeding), race, color, religion, ancestry or national origin, age, disability status, medical condition, marital
