Data Engineer

at  McDonalds Corporation

Company Description
McDonald’s is proud to be one of the most recognized brands in the world, with restaurants in over 100 countries that serve 70 million customers daily. We continue to operate from a position of strength. Our updated growth strategy is focused on staying ahead of what our customers want and realizing further growth potential. Our relentless ambition is why McDonald’s remains one of the world’s leading corporations after almost 70 years. Joining McDonald’s means thinking big and preparing for a career that can have influence around the world.
At McDonald’s, we see every day as a chance to create positive impact. We lead through our values centered on inclusivity, service, integrity, community and family. From support of Ronald McDonald House Charities to our Youth Opportunity project and sustainability initiatives, our values keep us dedicated to using our scale for good: good for our customers, people, industry and planet. We also offer a broad range of outstanding benefits including a sabbatical program, tuition assistance and flexible work arrangements.

We are enjoying the flexibility of a hybrid work model, in which employees spend part of their week connecting with co-workers in our state-of-the-art headquarters. Located in the booming West Loop of downtown Chicago, it’s set up to be a global hub that cultivates collaboration:

• Take a class at Hamburger University
• Sample future items in our Test Kitchen
• Utilize the latest technology to connect with your team around the globe

We are an equal opportunity employer committed to the diversity of our crew members, staff, operators, and suppliers. We promote an inclusive work environment that creates feel-good moments for everyone.
Job Description
We are looking for a Data Engineer to join our Data Science and Engineering team within Enterprise Data, Analytics and AI (EDAA). EDAA is responsible for turning the System’s data into a winning advantage, empowering a data-centric system, making faster and better decisions.

Responsibilities:

• Build data pipelines to ingest and integrate data from various sources into the organization’s data lake.
• Design and maintain data quality checks, identify, and resolve data quality issues in coordination with other teams.
• Develop CI/CD pipeline and automation to account for data, code and model changes.
• Develop and optimize complex SQL queries to extract and transform data from large and complex datasets.
• Collaborate globally with Data Scientists, MLOps, and Architects.
• Partner with the Data Governance team to enhance data capabilities.

Qualifications

• Bachelor’s degree in engineering, statistics, or other fields with a quantitative component is required
• 2+ years of experience in building and deploying data pipelines, preferably with ML platforms like Databricks or similar.
• 2+ years of Data Engineering within the context of Data Science, familiar with cloud platforms such as AWS.
• 2+ years coding advanced SQL and Python.
• Experience using big data batch and streaming tools such as Spark.
• Understanding of modern machine learning techniques.
• Experience working with data scientists for feature engineering and exploratory data analysis.
• Experience with continuous integration and deployment (CI/CD) frameworks.
• Strong knowledge of relational and multi-dimensional database architecture.
• Self-starter with a high level of intellectual curiosity and ability to set priorities.
• Strong analytical and problem-solving mindset.
• Ability to build trust and rapport, creating a comfortable and effective workplace.
• Strong verbal and written communication skills, with the ability to convey technical information to a non-technical audience.
• Comfortable with ambiguity and proactive in problem-solving.

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 status, sexual orientation, gender, gender identity, gender expression, transgender status, protected military or veteran status, citizenship status, genetic information, or any other characteristic protected by federal, state or local laws. This policy applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation and training.
Nothing in this job posting or description should be construed as an offer or guarantee of employment

• Build data pipelines to ingest and integrate data from various sources into the organization’s data lake.
• Design and maintain data quality checks, identify, and resolve data quality issues in coordination with other teams.
• Develop CI/CD pipeline and automation to account for data, code and model changes.
• Develop and optimize complex SQL queries to extract and transform data from large and complex datasets.
• Collaborate globally with Data Scientists, MLOps, and Architects.
• Partner with the Data Governance team to enhance data capabilities