Data Engineer

McDonald's - Chicago, IL

Full-time - Mid Level

Chicago, IL

Food Services and Drinking Places

About the position

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, and making faster and better decisions. As a Data Engineer, you will play a crucial role in building data pipelines that ingest and integrate data from various sources into the organization's data lake. You will design and maintain data quality checks, identify, and resolve data quality issues in coordination with other teams. Your expertise will be essential in developing CI/CD pipelines and automation to account for data, code, and model changes. Additionally, you will develop and optimize complex SQL queries to extract and transform data from large and complex datasets. Collaboration is key in this role, as you will work globally with Data Scientists, MLOps, and Architects. You will also partner with the Data Governance team to enhance data capabilities. This position requires a strong analytical and problem-solving mindset, as well as the ability to build trust and rapport with team members, creating a comfortable and effective workplace. Strong verbal and written communication skills are essential, as you will need to convey technical information to a non-technical audience. The ideal candidate will be a self-starter with a high level of intellectual curiosity and the ability to set priorities, comfortable with ambiguity and proactive in problem-solving.

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.

Requirements

• 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.

Benefits

• Sabbatical program
• Tuition assistance
• Flexible work arrangements